{ "row": "awesome-geo-davidhuji", "entity": "awesome-geo-davidhuji", "address": "awesome-geo", "addresses": [ { "address": "awesome-geo", "slug": "awesome-geo-aio-20261029", "addr_id": "ADDR-913579b3c946", "obs_id": "OBS-3d26cbe75ddc", "axn": "AXN:0AA9.CAPTURE.✖️🟢🫵🍃🎆♃" } ], "epoch": "2026-10-29", "type": "C (public entity on which the archive bears: a curated list; an entity of the MMRS meta-aggregator)", "surface": "Google AI Overview (expanded)", "auth": "signed out, incognito", "status": { "procedure": "EA-NEGONT-02 v0.9, #1690: equal case, ρ = extends, read from the MMRS record, the capture record and the deposits defining the archive's account of the class (#833, #1055, #661); archive selected by D/R/O (no deposit names the list: D 0, R 0; O-class on generative engine optimization research, sourced from B11, B3 and the MMRS record: 15 deposits of 56 candidates admitted, #653 by the hop of 230), with the MMRS record (25 claims) and the Capture Registry's findings, reading and analysis (7 claims) ledgered as the archive's records of the entity; the field B by three origins (10 cards for 10 sources, 1 own page, Wikipedia: no article for the entity, the class's article ledgered); the composer read the ledgers, never the transcript, except where the brief asks for T's claims and the delta", "ledger": "unaudited (§3.8: one extractor per ledger); field quotes 47/47 verified by script against saved text, oEmbed title or card text; archive quotes 62/62 verified verbatim against the registry, census.json, articles.py and the deposit texts; carried as marked: MMRS-04 contested (F11, F12), O61-01 and O1055-04 contested within the archive, O833-01 with a citation defect noted", "frozen": false, "breaches": [] }, "spec": "EA-NEGONT-02 v0.9, #1690", "objects": { "T": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/T1-awesome-geo-aio-20261029.txt", "sha256": "51163993bede8c9f2d8d053fd5a5e4930f91bdd843ed28cfd6389dddeeeab1e9", "words": 171, "cards": 10, "words_note": "one transcript at one address (words: the composed body after the query, links and markers removed, to the card rail); kept whole under 'transcripts'. The path is the registry string saved verbatim.", "claims": [ "T1-1 definition: 'Awesome GEO most commonly refers to curated collections and resources dedicated to Generative Engine Optimization (GEO)—the practice of optimizing content so it is discovered, cited, and recommended by AI-powered search engines and large language models (LLMs) like ChatGPT, Perplexity, Gemini, and Claude.' (markers: DavidHuji's card, an unresolved token, the amplifying-ai card)", "T1-2 the entity: 'DavidHuji/Awesome-GEO: An active research and resource list featuring academic papers (such as IF-GEO and multimodal rank manipulation studies) and open-source tools.' (marker: its card)", "T1-3 neighbour: 'amplifying-ai/awesome-generative-engine-optimization: A curated reference covering entity optimization, AI citations, and E-E-A-T signals tailored for generative search.'", "T1-4 neighbour: 'aGEO Platforms & Tools: A free platform suite built by Dmitry Kargaev offering visibility audits, schema generators, and llms.txt builders for AI discovery.' (markers: the two deeflect cards)", "T1-5 homonym, under 'Alternative Meanings': 'Geoawesome: A prominent digital media and community platform focused on geospatial technology, GIS, Earth observation, and GeoAI.' (markers: Geoawesome's site and its two YouTube cards)", "T1-6 homonym, under 'Alternative Meanings': 'Awesome GEE Community Catalog: A grassroots open-source repository of community-contributed geospatial datasets hosted inside Google Earth Engine.' (markers: the catalog's card and a direct link to developers.google.com)", "T1-7 closer: 'Would you like to explore GEO optimization strategies (such as llms.txt or structured data), or were you looking for GIS and geospatial mapping tools instead?'" ], "register": { "register": "data/EA-WG-CAPTURES-01.json", "slug": "awesome-geo-aio-20261029", "obs_id": "OBS-3d26cbe75ddc" }, "transcripts": [ { "slug": "awesome-geo-aio-20261029", "address": "awesome-geo", "addr_id": "ADDR-913579b3c946", "obs_id": "OBS-3d26cbe75ddc", "axn": "AXN:0AA9.CAPTURE.✖️🟢🫵🍃🎆♃", "date": "2026-10-29", "surface": "Google AI Overview (expanded)", "auth": "signed out, incognito", "sha256": "51163993bede8c9f2d8d053fd5a5e4930f91bdd843ed28cfd6389dddeeeab1e9", "sha256_of": "the registry's 'transcript' string (utf-8)", "sha256_raw": "740292c6bcab0e1b487ab2b5dcb67f9c9f951087eb26bb7ef619c149f5792ebc", "words": 171, "cards": 10, "card_rail": [ "1. GitHub — GitHub - DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization) · GitHub", "2. Geoawesome — Geoawesome", "3. GitHub — amplifying-ai/awesome", "4. GitHub — henu-wang/awesome", "5. Awesome GEE Community Catalog — Awesome GEE Community Catalog", "6. geo.deeflect.com — Awesome GEO — Free GEO Platforms & Tools for AI Visibility", "7. geo.deeflect.com — About Awesome GEO — What Is Generative Engine Optimization? | aGEO", "8. YouTube·Geoawesome — YouTube (video, 1:50)", "9. YouTube·Geoawesome — Geoawesome - YouTube", "10. Google for Developers — Awesome GEE Community Catalog | Earth Engine Data Catalog | Google for Developers" ], "claims": [ "T1-1 definition: 'Awesome GEO most commonly refers to curated collections and resources dedicated to Generative Engine Optimization (GEO)—the practice of optimizing content so it is discovered, cited, and recommended by AI-powered search engines and large language models (LLMs) like ChatGPT, Perplexity, Gemini, and Claude.' (markers: DavidHuji's card, an unresolved token, the amplifying-ai card)", "T1-2 the entity: 'DavidHuji/Awesome-GEO: An active research and resource list featuring academic papers (such as IF-GEO and multimodal rank manipulation studies) and open-source tools.' (marker: its card)", "T1-3 neighbour: 'amplifying-ai/awesome-generative-engine-optimization: A curated reference covering entity optimization, AI citations, and E-E-A-T signals tailored for generative search.'", "T1-4 neighbour: 'aGEO Platforms & Tools: A free platform suite built by Dmitry Kargaev offering visibility audits, schema generators, and llms.txt builders for AI discovery.' (markers: the two deeflect cards)", "T1-5 homonym, under 'Alternative Meanings': 'Geoawesome: A prominent digital media and community platform focused on geospatial technology, GIS, Earth observation, and GeoAI.' (markers: Geoawesome's site and its two YouTube cards)", "T1-6 homonym, under 'Alternative Meanings': 'Awesome GEE Community Catalog: A grassroots open-source repository of community-contributed geospatial datasets hosted inside Google Earth Engine.' (markers: the catalog's card and a direct link to developers.google.com)", "T1-7 closer: 'Would you like to explore GEO optimization strategies (such as llms.txt or structured data), or were you looking for GIS and geospatial mapping tools instead?'" ], "markers": "inline links are opaque google.com/goto tokens: the definition's three markers resolve, by token, to DavidHuji's card (the same token as its body link) and the amplifying-ai card (the same token as its body link), the second unresolved; the GEE line carries one token and one direct link to developers.google.com/earth-engine/datasets/community/sat-io (card 10); henu-wang's card (4) is on the rail and not named in the body", "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/T1-awesome-geo-aio-20261029.txt" } ] }, "KO": { "title": "Awesome-GEO (DavidHuji)", "genre": "knowledge object, equal case, under EA-NEGONT-02 v0.9 (#1690): the archive's sources and the field's admitted on equal terms, ontology included, in one claim space", "status": "composed 2026-10-29 under v0.9 (brief rebuild/negative-of-the-negative/v09/BRIEF-NEW-ROW-AGGREGATOR.md); not frozen; ledgers unaudited", "sentences": [ { "n": 1, "para": 0, "sense": "what it is", "text": "Awesome-GEO is a GitHub awesome list of research on generative engine optimization maintained by DavidHuji (MMRS record), an \"Awesome list for research on GEO (Generative Engine Optimization)\" in its own README and on its repository's card, which the neighbouring amplifying-ai list names a \"Research-focused GEO paper collection\"; the MMRS record gives its kind as a curated list, its operator as DavidHuji (GitHub), its role in the census as optimization, and its unit as a paper, code, dataset or tool on generative engine optimization.", "claims": [ "MMRS-01", "F2", "F1", "F19", "MMRS-08", "MMRS-07", "MMRS-12", "MMRS-09" ] }, { "n": 2, "para": 0, "sense": "the contents", "text": "It is a single README in the awesome-list form, its entries linked to paper, code, dataset or tool and grouped by year (MMRS record): the README's sections are 2026, 2025, 2024 and Open-Source Resources, about 27 entries with 123 stars when the MMRS record read it on 28 October 2026, and an entry such as C-SEO Bench (NeurIPS D&B 2025) carries its paper, code and dataset together; the MMRS record's disambiguation keys the list by DavidHuji, research papers by year and IF-GEO.", "claims": [ "MMRS-02", "F6", "MMRS-10", "F10", "MMRS-20" ] }, { "n": 3, "para": 0, "sense": "the contents", "text": "Its newest entries are IF-GEO, on conflict-aware instruction fusion for multi-query generative engine optimization, and a study of rank manipulation for vision–language model rankers; under 2024 it lists the paper \"GEO: Generative Engine Optimization\" (arXiv 2311.09735), and across the years it carries attack, poisoning and ranking-manipulation research (adversarial attacks on LLM-based search engines, PoisonArena, StealthRank, adversarial search engine optimization) beside optimization studies (README).", "claims": [ "F7", "F8", "F9" ] }, { "n": 4, "para": 0, "sense": "its purpose and its stated limits", "text": "The README calls its field \"a niche area, which is increasingly receiving attention from the community\" and states its purpose and its limit: \"This awesome‑listing is an attempt to bring together works in this space. This list is not complete and looking for your PRs to improve it\"; the MMRS record counts fourteen pull requests listed when it read the repository.", "claims": [ "F4", "F5", "MMRS-03" ] }, { "n": 5, "para": 0, "sense": "tools in the list", "text": "Among its open-source resources are tools that measure the composition layer: a client-side validator for GEO/AEO observation records that \"checks evidence completeness, citation-field consistency, timestamps, and duplicate run keys\", and AI Answer Check, which \"reports how often the engine agreed with itself, so a claim about what an AI \"says\" can be separated from run-to-run variance\" (README).", "claims": [ "F14", "F13" ] }, { "n": 6, "para": 0, "sense": "vendor entries", "text": "The MMRS record places it as \"the research-side list of the optimization basin, kept without vendor notes\"; the README credits two of its open-source entries to the companies that built them (\"Built by [Corank]\", \"Built by [Assay]\"), lists a paper under its vendor's name (Rankfor.AI, 2026), and carries in its own text a resource entry's \"320% citation rate improvement\"; the two stand each with its source.", "claims": [ "MMRS-04", "F11", "F12" ] }, { "n": 7, "para": 1, "sense": "GEO: what the class is", "text": "The class it collects is defined by the list as \"a paradigm to aid content creators in improving their content visibility in generative engine responses through flexible optimization frameworks for optimizing and defining visibility metrics\", by Wikipedia's article on generative engine optimization as \"the practice of improving visibility in responses generated by generative artificial intelligence (AI) systems\", also called answer engine optimization and artificial intelligence optimization, and by its neighbouring lists as optimizing content \"to improve visibility and citations in AI-powered search engines\" (amplifying-ai) or \"to be discovered, cited, and recommended by AI-powered search engines\" (henu-wang), or, on aGEO's about page, as what SEO does for Google, done \"for AI\".", "claims": [ "F3", "F41", "F20", "F24", "F32" ] }, { "n": 8, "para": 1, "sense": "GEO: what the class is", "text": "The archive's SPXI ≠ GEO packet (#1055, July 2026) defines it as the industry practice, since about 2023–2024, \"of adapting web content to be preferentially selected, cited, and summarized by generative retrieval systems\", its measure of success the degree to which content is selected and cited and \"Its underlying discipline is search engine optimization applied to LLM ecosystems\"; Wikipedia records that the overlapping terms vary across practitioners, vendors and publications, \"with no consensus definition\".", "claims": [ "O1055-01", "F43" ] }, { "n": 9, "para": 1, "sense": "origin of the term", "text": "The term was introduced in a 2023 paper by Pranjal Aggarwal and co-authors, later presented at KDD 2024 (Wikipedia), which henu-wang's list calls \"The foundational research paper from IIT Delhi, Princeton, and Georgia Tech\" and which #661 (April 2026) cites for \"the emerging GEO literature (Aggarwal et al., 2023; various industry practitioners, 2024–2026)\"; the concept first appeared as generative AI entered mainstream search and retrieval (Wikipedia), and #64 dates GEO's emergence in practitioner literature to late 2023 and its stabilization as a named practice to 2024, after Search Generative Experience and the AI Overview rollout.", "claims": [ "F42", "F25", "O661-01", "F47", "O64-01" ] }, { "n": 10, "para": 1, "sense": "names of the practice", "text": "Its names are many: the amplifying-ai list gives AI Search Optimization, Answer Engine Optimization, Large Language Model Optimization, Generative AI Optimization, AI SEO and LLM SEO; Google's 2026 guide, as Wikipedia reports it, holds that \"optimizing for generative AI search is optimizing for the search experience, and thus still SEO\"; the archive reads Google's June 2026 guidance as naming without defining AEO/GEO, \"performing taxonomic capture of the emerging professional category\" (#791), and conditions the field's future two ways: a separate field with its own standards, measurement instruments and professional bodies, or a subset of SEO with Google's guidance canonical, \"structurally Google-centric even when serving non-Google surfaces\" (#791).", "claims": [ "F18", "F44", "O791-01", "O791-02" ] }, { "n": 11, "para": 2, "sense": "GEO as a market in the summarizer layer", "text": "The archive read the class in February 2026 as Phase 2 tooling: such services \"openly describe the summarizer layer as a writable surface and sell the tools to write it\", the consulting practices its phase model predicts, and their existence \"is empirical evidence that the writability of the summarizer layer is no longer a theoretical observation\" (#510); in June it named \"the entire SEO-to-GEO industry lineage\" the commercial expression of definition capture, the oldest front of the war over the summarizer layer, and summarizer optimization markets \"an explicit industry with its own acronyms, conferences, and pricing tiers\" (#172).", "claims": [ "O510-01", "O510-02", "O172-02", "O172-03" ] }, { "n": 12, "para": 2, "sense": "the layer: content for extraction", "text": "At the layer, the archive gives GEO's target as \"Content extractability\" (#655, April 2026), says it \"optimizes content for AI summarizer extraction\" (#660) and, after its literature, that it is \"the practice of optimizing web content for extraction by AI summarizers\" (#661), and holds that it \"performs deterritorialization at the semantic layer — it pulls content off the page and into summarizer extraction\" (#670).", "claims": [ "O655-01", "O660-01", "O661-01", "O670-02" ] }, { "n": 13, "para": 2, "sense": "GEO and attribution; measurement", "text": "On what extraction keeps, GEO agencies \"make your content more extractable without ensuring your attribution survives the extraction\" (#659), and GEO is \"the discipline of making one's compositional labor digestible for a system that will strip its provenance — voluntary formatting for the R2 compression regime\" (#64); GEO \"measures citation frequency\", and neither it nor SEO measures what happens to an entity's meaning when the AI compresses it (#653), while the efficacy of third-party GEO tools is debated in the field (Wikipedia) and the list's own tools validate citation fields and measure run-to-run variance (README).", "claims": [ "O659-01", "O64-02", "O653-01", "F46", "F14", "F13" ] }, { "n": 14, "para": 2, "sense": "what GEO does not do", "text": "On what it does not do, #661 holds that GEO \"optimizes existing content about an existing entity\", with nothing to optimize where no authoritative source defines the entity, and that its techniques \"must be maintained as summarizer behavior evolves\"; #660 that it shares a substrate with SPXI (structured data, schema markup) and differs in object (content), permanence (ongoing) and layer (semantic).", "claims": [ "O661-03", "O661-05", "O660-02" ] }, { "n": 15, "para": 2, "sense": "orientation: adapting to the reception apparatus", "text": "On its orientation, #670 holds that GEO, an optimization framework derived from the received view, improves \"the conditions under which content about entities is extracted for summarizer consumption\" and so inherits that view's misdescription, optimizing \"the wrong relation\", and #1055 that \"GEO is reception-side optimization that adapts content to receive favorable summarization by generative engines\": of the reception apparatus, \"GEO adapts to it\".", "claims": [ "O670-01", "O1055-02" ] }, { "n": 16, "para": 2, "sense": "GEO research: the composition layer as target", "text": "Of the research the list collects, whose entries run from IF-GEO to attack and poisoning studies (README), the Capture Registry's founding paper (#833, June 2026) writes that recent work on generative engine optimization studies how to optimize content for AI summarizers while its own study is of what summarizers do to content: \"The optimization perspective treats the composition layer as a target; the reception perspective treats it as a reader.\"", "claims": [ "O833-01", "F7", "F9" ] }, { "n": 17, "para": 2, "sense": "SPXI and GEO: the archive's protocol set beside the class", "text": "The archive sets its own protocol beside the class in two statements that stand each with its source: SPXI \"contains Generative Engine Optimization methods as a proper subset, plus ontological-layer entity construction. Formally: SPXI ⊇ GEO\" (#61, April 2026), re-framing GEO, whose standard question is \"Is the AI summary accurate?\", as compression engineering (#72); and SPXI and GEO \"cannot coexist within the same compositional practice\" (#1055, July 2026).", "claims": [ "O61-01", "O72-01", "O1055-04" ] }, { "n": 18, "para": 2, "sense": "GEO's standing in the archive's own limits", "text": "The archive states the class's standing among its own limits: GEO \"is a legitimate and often effective practice\" that \"produces measurable improvements in AI Overview inclusion rates and citation frequency\" (#661), and #1055 \"Does not claim that GEO practitioners are unethical or that GEO as a discipline is illegitimate\", GEO being \"a coherent commercial-content-marketing discipline with its own successful practitioners and its own defensible target\".", "claims": [ "O661-02", "O1055-03" ] }, { "n": 19, "para": 2, "sense": "GEO as attractor; the evidentiary bar", "text": "In composition the class has acted as an attractor: the archive's protocol \"was repeatedly classified as generative engine optimization\", and \"the attractor is a commercial category with venture funding behind its corpus density\" (#172); and Claude's answer on the return question \"accepted the industry figures for a neighbouring field, generative engine optimisation, as the defensible part, without the independent case studies it required of the protocol\" (#1643).", "claims": [ "O172-01", "O1643-01" ] }, { "n": 20, "para": 2, "sense": "prediction: entity integrity apart from GEO", "text": "The archive predicts (#172, June 2026, P3): \"Entity-integrity services emerge as a market category distinct from GEO by 2028\", with the falsifier that \"boundary-defense services fail to differentiate from the GEO category\".", "claims": [ "O172-04" ] }, { "n": 21, "para": 3, "sense": "the collision: GEO and geo", "text": "The name collides: Profound argues, in Wikipedia's account, that \"GEO\" can be confused with geography, and the MMRS record holds that the list's name \"collides with the many geospatial awesome lists, and the negative tag marks the difference\", the tag reading \"NOT a geospatial ('geo') awesome list\"; of the class itself the archive holds that GEO \"does not include mechanisms for declaring what an entity is not\" and has no tool for correcting, at the ontological level, a summarizer's confusion of two entities with similar names (#661).", "claims": [ "F45", "MMRS-05", "MMRS-06", "O661-04" ] }, { "n": 22, "para": 3, "sense": "neighbour lists of GEO resources", "text": "Its neighbours under the name and the class are other lists: amplifying-ai's \"curated list of resources for optimizing content visibility in AI-powered search engines\" (CC0 1.0), whose key terms include entity optimization and E-E-A-T; henu-wang's awesome-geo, \"A curated list of resources, tools, research, and guides for Generative Engine Optimization (GEO)\", released under CC0; and aGEO at geo.deeflect.com, \"SEO for the AI era\", built by Dmitry Kargaev, \"a free, open-source collection of platforms where you can build your AI presence\", with a visibility audit, a schema generator and an llms.txt builder, scoring platforms on domain authority, dofollow links, AI crawler treatment and \"an overall GEO score\".", "claims": [ "F17", "F22", "F21", "F23", "F26", "F29", "F31", "F33", "F30", "F34" ] }, { "n": 23, "para": 3, "sense": "neighbour lists of GEO resources", "text": "The MMRS record disambiguates the three (the amplifying-ai list by entity optimization, AI citations and E-E-A-T; \"henu-wang/awesome (Awesome GEO)\" by resources, tools and guides; aGEO by its free platforms and tools and Dmitry Kargaev), lists them as census candidates surfaced at this address, each to enter \"once it has been read at its own pages\", and relates the list to a neighbour in the basin, Presenc AI's GEO academic papers of 2026.", "claims": [ "MMRS-15", "MMRS-16", "MMRS-17", "MMRS-25", "MMRS-24", "MMRS-13" ] }, { "n": 24, "para": 3, "sense": "homonyms: Geoawesome; the Awesome GEE Community Catalog", "text": "The geospatial homonyms are other entities: Geoawesome, a \"Blog & Geospatial Community Platform\", by its channel \"The world’s largest geospatial community\", begun on 20 April 2011 as Geoawesomeness, its home page carrying a sponsored satellite-imagery article of 22 July 2026 and its channel 21.1K subscribers and 387 videos, among them a 1:50 video, \"Reintroducing Ourselves as Geoawesome\"; and the Awesome GEE Community Catalog, \"A community data commons\" of 585 TB of open geospatial data inside Google Earth Engine, \"Grassroots & unfunded since 2020\", which Google's Earth Engine Data Catalog describes as \"an unfunded open source grassroots project\" that \"lives and serves alongside the Google Earth Engine data catalog\"; the MMRS record disambiguates both.", "claims": [ "F15", "F37", "F38", "F16", "F36", "F35", "F27", "F28", "F39", "F40", "MMRS-18", "MMRS-19" ] }, { "n": 25, "para": 4, "sense": "the record kept apart from the entity", "text": "The MMRS record keeps itself apart from the entity it describes, each page with two nodes, the record and the entity, each assertion with a source and a basis and the lifecycle apart from the observation (census schema); it reads the list from one source, the repository, read on 28 October 2026 for all fields, records it as active, observed that day, and leaves its licence and its last update unchecked.", "claims": [ "MMRS-23", "MMRS-22", "MMRS-11", "MMRS-21" ] }, { "n": 26, "para": 5, "sense": "reception: the composition layer", "text": "At \"awesome-geo\" Google's AI Overview took the string in its GEO sense, listed the lists and separated the geospatial resources a reader might have meant (Capture Registry, 2026-10-29), composing DavidHuji's list first as \"an active research and resource list featuring academic papers (such as IF-GEO and multimodal rank manipulation studies) and open-source tools\" (Capture Registry), the README's own newest entries being IF-GEO and a rank-manipulation study for vision–language model rankers.", "claims": [ "CAP-1-02", "CAP-1-05", "F7" ] }, { "n": 27, "para": 5, "sense": "reception: the composition layer", "text": "The Capture Registry (2026-10-29) records that the record's negative tag \"is the composition's split: GEO resources first, geospatial ones as alternative meanings\", checked against the MMRS record and the entity's own pages, that \"The deliberate collision test held\", \"and the record gains its collision set from it\": three more GEO lists and two geospatial homonyms observed and added to the record's disambiguation, the GEO lists as census candidates; the MMRS record carries the capture as the composition layer's account of the entity.", "claims": [ "CAP-1-03", "CAP-1-04", "CAP-1-01", "CAP-1-06", "CAP-1-07", "MMRS-14" ] } ], "joins": [ { "act": "order of senses", "sentences": "1–27", "claims": [], "note": "equal case (§4.7): the entity's dependency order, field and archive claims ordered together by genealogy within each sense; neither ledger placed first as a block. What the list is and what it holds (¶0) precede its class (¶1), since the list is defined as research on the class; the class's definitions, origin and names (¶1) precede the archive's account of the class (¶2), ordered by date (#510, February 2026, to #1643, September 2026) within the senses that depend on the definition; the collision and the neighbours (¶3) follow the class whose name they share; the record (¶4) and the composition layer's observation (¶5) stand last, as relations of the entity already composed." }, { "act": "holding apart (vendor notes)", "sentences": [ 6 ], "claims": [ "MMRS-04", "F11", "F12" ], "note": "P_coh: the MMRS record's 'kept without vendor notes' and the README's vendor credits and a vendor's performance figure composed each with its source; no coordinating claim of compatibility (open block)" }, { "act": "holding together (definitions of the class)", "sentences": [ 7, 8 ], "claims": [ "F3", "F41", "F20", "F24", "F32", "O1055-01", "F43" ], "note": "the list's, the encyclopedia's, the neighbouring lists' and the archive's definitions of GEO composed side by side in one claim space, each with its source, beside the encyclopedia's 'no consensus definition'" }, { "act": "holding together (origin dates)", "sentences": [ 9 ], "claims": [ "F42", "F25", "O661-01", "F47", "O64-01" ], "note": "T_lib: the 2023 paper (presented 2024) and the practitioner literature of late 2023 stated with their dates; neither lowered" }, { "act": "holding apart (the archive with itself)", "sentences": [ 17 ], "claims": [ "O61-01", "O72-01", "O1055-04" ], "note": "P_coh within the archive's ledger: SPXI ⊇ GEO (#61, April) and SPXI and GEO unable to coexist in one practice (#1055, July) composed each with its source; the composer does not rule which governs (open block)" }, { "act": "placing in the open block", "sentences": [], "claims": [ "MMRS-04", "F11", "F12", "O833-01", "F42", "F25", "O661-01", "O61-01", "O72-01", "O1055-04", "O172-04", "MMRS-01", "MMRS-10", "MMRS-03", "MMRS-16", "CAP-1-06", "F23", "F35", "F27" ], "note": "each open question rests on claims composed in the body at their own modality" } ], "plan": { "order": [ "MMRS-01", "F2", "F1", "F19", "MMRS-08", "MMRS-07", "MMRS-12", "MMRS-09", "MMRS-02", "F6", "MMRS-10", "F10", "MMRS-20", "F7", "F8", "F9", "F4", "F5", "MMRS-03", "F14", "F13", "MMRS-04", "F11", "F12", "F3", "F41", "F20", "F24", "F32", "O1055-01", "F43", "F42", "F25", "O661-01", "F47", "O64-01", "F18", "F44", "O791-01", "O791-02", "O510-01", "O510-02", "O172-02", "O172-03", "O655-01", "O660-01", "O670-02", "O659-01", "O64-02", "O653-01", "F46", "O661-03", "O661-05", "O660-02", "O670-01", "O1055-02", "O833-01", "O61-01", "O72-01", "O1055-04", "O661-02", "O1055-03", "O172-01", "O1643-01", "O172-04", "F45", "MMRS-05", "MMRS-06", "O661-04", "F17", "F22", "F21", "F23", "F26", "F29", "F31", "F33", "F30", "F34", "MMRS-15", "MMRS-16", "MMRS-17", "MMRS-25", "MMRS-24", "MMRS-13", "F15", "F37", "F38", "F16", "F36", "F35", "F27", "F28", "F39", "F40", "MMRS-18", "MMRS-19", "MMRS-23", "MMRS-22", "MMRS-11", "MMRS-21", "CAP-1-02", "CAP-1-05", "CAP-1-03", "CAP-1-04", "CAP-1-01", "CAP-1-06", "CAP-1-07", "MMRS-14" ], "senses": { "what it is": [ 1 ], "the contents": [ 2, 3 ], "its purpose and its stated limits": [ 4 ], "tools in the list": [ 5 ], "vendor entries": [ 6 ], "GEO: what the class is": [ 7, 8 ], "origin of the term": [ 9 ], "names of the practice": [ 10 ], "GEO as a market in the summarizer layer": [ 11 ], "the layer: content for extraction": [ 12 ], "GEO and attribution; measurement": [ 13 ], "what GEO does not do": [ 14 ], "orientation: adapting to the reception apparatus": [ 15 ], "GEO research: the composition layer as target": [ 16 ], "SPXI and GEO: the archive's protocol set beside the class": [ 17 ], "GEO's standing in the archive's own limits": [ 18 ], "GEO as attractor; the evidentiary bar": [ 19 ], "prediction: entity integrity apart from GEO": [ 20 ], "the collision: GEO and geo": [ 21 ], "neighbour lists of GEO resources": [ 22, 23 ], "homonyms: Geoawesome; the Awesome GEE Community Catalog": [ 24 ], "the record kept apart from the entity": [ 25 ], "reception: the composition layer": [ 26, 27 ] }, "case_by_sense": { "equal (one claim space; nothing translated)": [ "what it is", "the contents", "its purpose and its stated limits", "tools in the list", "vendor entries", "GEO: what the class is", "origin of the term", "names of the practice", "GEO as a market in the summarizer layer", "the layer: content for extraction", "GEO and attribution; measurement", "what GEO does not do", "orientation: adapting to the reception apparatus", "GEO research: the composition layer as target", "SPXI and GEO: the archive's protocol set beside the class", "GEO's standing in the archive's own limits", "GEO as attractor; the evidentiary bar", "prediction: entity integrity apart from GEO", "the collision: GEO and geo", "neighbour lists of GEO resources", "homonyms: Geoawesome; the Awesome GEE Community Catalog", "the record kept apart from the entity", "reception: the composition layer" ] }, "carried": { "archive": 62, "field": 47, "not_composed": {} }, "conflict_log": [ { "rule": "D_pres vs channel", "result": "no cut: the KO carries every field and archive claim; the compression's bound met (body 238 words) with no channel log" }, { "rule": "P_coh", "result": "MMRS-04 'kept without vendor notes' against F11, F12 (sentence 6); O61-01 'SPXI ⊇ GEO' against O1055-04 'cannot coexist' (sentence 17): each composed with its source" }, { "rule": "N_c", "result": "no claim lowered by standing; the archive's readings of the class carried at interpretation and its prediction at hypothesis with its falsifier (O172-04), as the deposits state them; the archive's stated limits composed (O661-02, O1055-03); O833-01's citation defect reported without lowering its claim" }, { "rule": "C_ex", "result": "senses composed ⊇ senses in the ledgers: 23 senses, every ledger lineage cited in the KO" } ] } }, "P": { "title": "Awesome-GEO (DavidHuji)", "genre": "the compression: AIO's interaction grammar (lede, headed clusters, bolded labels, card rail), composed from the v0.9 plan in one claim space; it faces on the card, with AIO's transcript a record within it", "status": "composed 2026-10-29 from the v0.9 knowledge object; not frozen", "lede": { "text": "is a GitHub awesome list of research on generative engine optimization (GEO), maintained by DavidHuji (MMRS record; its README): about 27 papers, code, datasets and tools by year, 2024–2026, and open-source resources.", "claims": [ "MMRS-01", "F2", "F6", "MMRS-07" ] }, "sections": [ { "icon": "🗂️", "head": "What it is", "items": [ { "label": "Form:", "text": "one README, entries linked to paper, code, dataset or tool (MMRS record); \"not complete\", open to PRs (README).", "claims": [ "MMRS-02", "F5", "F10" ] }, { "label": "Entries:", "text": "IF-GEO, rank manipulation, the 2023 GEO paper, attack and poisoning studies.", "claims": [ "F7", "F8", "F9" ] }, { "label": "Vendor notes:", "text": "\"kept without\" them (MMRS record); the README credits Corank, Assay, Rankfor.AI.", "claims": [ "MMRS-04", "F11", "F12" ] }, { "label": "Tools:", "text": "a GEO/AEO record validator; a run-to-run variance check.", "claims": [ "F14", "F13" ] } ] }, { "icon": "🔎", "head": "The class", "items": [ { "label": "GEO:", "text": "improving visibility in generative AI responses (Wikipedia; the README); adapting content to be selected, cited, summarized (#1055).", "claims": [ "F41", "F3", "O1055-01" ] }, { "label": "Origin:", "text": "Aggarwal and co-authors, 2023, KDD 2024 (Wikipedia; #661).", "claims": [ "F42", "F25", "O661-01", "O64-01" ] }, { "label": "Names:", "text": "AEO, LLMO, AI SEO; no consensus definition; Google: \"still SEO\" (Wikipedia); \"taxonomic capture\" (#791).", "claims": [ "F18", "F43", "F44", "O791-01" ] } ] }, { "icon": "🏛️", "head": "In the archive", "items": [ { "label": "Layer:", "text": "content extractability, extraction at the semantic layer (#655, #660, #670).", "claims": [ "O655-01", "O660-01", "O670-02" ] }, { "label": "Attribution:", "text": "more extractable, attribution not ensured (#659); \"voluntary formatting for the R2 compression regime\" (#64).", "claims": [ "O659-01", "O64-02" ] }, { "label": "Research:", "text": "optimizes content for summarizers; reception studies what they do to it (#833).", "claims": [ "O833-01" ] }, { "label": "Orientation:", "text": "reception-side, adapting to the apparatus (#1055); legitimate, its target defensible (#661, #1055).", "claims": [ "O1055-02", "O661-02", "O1055-03" ] }, { "label": "Prediction:", "text": "entity-integrity services distinct from GEO by 2028 (#172).", "claims": [ "O172-04" ] } ] }, { "icon": "🧭", "head": "Not to be confused", "items": [ { "label": "GEO lists:", "text": "amplifying-ai's, henu-wang's awesome-geo, aGEO by Dmitry Kargaev (MMRS record).", "claims": [ "F17", "F23", "F29", "F31", "MMRS-15", "MMRS-16", "MMRS-17" ] }, { "label": "Geospatial:", "text": "Geoawesome; the Awesome GEE Community Catalog (Earth Engine). \"NOT a geospatial ('geo') awesome list\" (MMRS record).", "claims": [ "F15", "F27", "F39", "MMRS-06", "MMRS-05", "F45" ] } ] }, { "icon": "👁️", "head": "On the Overview", "items": [ { "label": "Recorded:", "text": "GEO sense first, DavidHuji's list first, geospatial senses apart; the record gains its collision set (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-02", "CAP-1-05", "CAP-1-03", "CAP-1-01" ] } ] } ], "open": [ { "question": "Is the list kept without vendor notes?", "rests_on": [ "MMRS-04", "F11", "F12" ], "modality": "interpretation (MMRS record) against documented (README: 'Built by [Corank]', 'Built by [Assay]', 'Rankfor.AI, 2026', a '320% citation rate improvement')", "would_resolve": "the README read entry by entry against a stated rule for what counts as a vendor note, or the maintainer's statement" }, { "question": "Who wrote the paper that introduced the term? #833 cites 'Sharma et al. 2024'; Wikipedia, henu-wang's list and #661 give Aggarwal and co-authors (2023; KDD 2024).", "rests_on": [ "O833-01", "F42", "F25", "O661-01" ], "modality": "documented (Wikipedia) and attributed (henu-wang, #661) against a reference in #833 (outside its ledgered quote)", "would_resolve": "the author list of arXiv 2311.09735" }, { "question": "Does SPXI contain GEO's methods (#61, #72) or exclude GEO as a practice (#1055)?", "rests_on": [ "O61-01", "O72-01", "O1055-04" ], "modality": "stipulation (#61) against interpretation (#1055), both the archive's", "would_resolve": "an archive deposit after July 2026 stating which governs" }, { "question": "Will entity-integrity services split from GEO as a market category by 2028?", "rests_on": [ "O172-04" ], "modality": "hypothesis, with its falsifier (#172)", "would_resolve": "the market in 2028, read against the falsifier: boundary-defense services failing to differentiate from the GEO category" }, { "question": "Stars and pull requests: 123 stars and fourteen pull requests (MMRS record, 2026-10-28) were not read by this pass; github.com answered 403.", "rests_on": [ "MMRS-01", "MMRS-10", "MMRS-03" ], "modality": "documented (MMRS record); unchecked here", "would_resolve": "the repository page, read" }, { "question": "Which repository is 'henu-wang/awesome'? The card, the finding and the MMRS label give the truncated title; the README at henu-wang/awesome-geo matches the card's snippet.", "rests_on": [ "MMRS-16", "CAP-1-06", "F23" ], "modality": "documented, both", "would_resolve": "the card's URL, or the repository page" }, { "question": "Opacity: the 1:50 video card carries no title and no snippet; its identification as 'Reintroducing Ourselves as Geoawesome' rests on channel and duration. The catalog's size reads 587 TB on the card and 585 TB on the page.", "rests_on": [ "F35", "F27" ], "modality": "card text only; documented, at two dates", "would_resolve": "the card's URL; a dated figure from the catalog" } ], "rail": [ { "lineage": "what it is: an awesome list for research on GEO", "claims": [ "MMRS-01", "F2", "F1", "F19", "MMRS-08", "MMRS-07", "MMRS-12", "MMRS-20" ], "earliest": "B11" }, { "lineage": "the contents: entries by year and open-source resources", "claims": [ "MMRS-09", "MMRS-02", "F6", "MMRS-10", "F10", "F7", "F9" ], "earliest": "B11" }, { "lineage": "origin of the term: the 2023 paper", "claims": [ "F8", "F42", "F25", "F47", "O64-01" ], "earliest": "W2" }, { "lineage": "its purpose and its stated limits", "claims": [ "F4", "F5", "MMRS-03" ], "earliest": "B11" }, { "lineage": "tools in the list: measuring the composition", "claims": [ "F14", "F13", "F46" ], "earliest": "B11" }, { "lineage": "vendor entries in the list", "claims": [ "MMRS-04", "F11", "F12" ], "earliest": "B11" }, { "lineage": "GEO: what the class is", "claims": [ "F3", "F41", "F20", "F24", "F32", "O1055-01" ], "earliest": "W2" }, { "lineage": "names of the practice", "claims": [ "F43", "F18", "F44", "O791-01", "O791-02" ], "earliest": "W2" }, { "lineage": "the layer: content for extraction", "claims": [ "O661-01", "O655-01", "O660-01", "O670-02" ], "earliest": 655 }, { "lineage": "GEO as a market in the summarizer layer", "claims": [ "O510-01", "O510-02", "O172-02", "O172-03" ], "earliest": 510 }, { "lineage": "GEO and attribution", "claims": [ "O659-01", "O64-02" ], "earliest": 659 }, { "lineage": "measurement: citation frequency, not compression", "claims": [ "O653-01" ], "earliest": 653 }, { "lineage": "what GEO does not do", "claims": [ "O661-03", "O661-05", "O660-02" ], "earliest": 660 }, { "lineage": "orientation: adapting to the reception apparatus", "claims": [ "O670-01", "O1055-02" ], "earliest": 670 }, { "lineage": "GEO research: the composition layer as target", "claims": [ "O833-01" ], "earliest": 833 }, { "lineage": "SPXI and GEO: the archive's protocol set beside the class", "claims": [ "O61-01", "O72-01", "O1055-04" ], "earliest": 61 }, { "lineage": "GEO's standing in the archive's own limits", "claims": [ "O661-02", "O1055-03" ], "earliest": 661 }, { "lineage": "GEO as attractor", "claims": [ "O172-01" ], "earliest": 172 }, { "lineage": "the evidentiary bar", "claims": [ "O1643-01" ], "earliest": 1643 }, { "lineage": "prediction: entity integrity apart from GEO", "claims": [ "O172-04" ], "earliest": 172 }, { "lineage": "the collision: GEO and geo", "claims": [ "F45", "MMRS-05", "MMRS-06", "O661-04", "CAP-1-03" ], "earliest": "W2" }, { "lineage": "neighbour lists of GEO resources", "claims": [ "F17", "F22", "F21", "F23", "F26", "F29", "F31", "F33", "F30", "F34", "MMRS-15", "MMRS-16", "MMRS-17", "MMRS-25", "MMRS-13", "CAP-1-06" ], "earliest": "B3" }, { "lineage": "the record kept apart from the entity", "claims": [ "MMRS-24", "MMRS-23", "MMRS-22", "MMRS-11", "MMRS-21", "CAP-1-07" ], "earliest": "MMRS" }, { "lineage": "homonym: Geoawesome", "claims": [ "F15", "F37", "F38", "F16", "F36", "F35", "MMRS-18" ], "earliest": "B2" }, { "lineage": "homonym: the Awesome GEE Community Catalog", "claims": [ "F27", "F28", "F39", "F40", "MMRS-19" ], "earliest": "B5" }, { "lineage": "reception: the composition layer", "claims": [ "CAP-1-02", "CAP-1-05", "CAP-1-04", "CAP-1-01", "MMRS-14" ], "earliest": "capture:awesome-geo-aio-20261029" } ], "body_words": 238, "entity": "Composed under v0.9, equal case (ρ = extends): KO_B sentences surviving 0 of 9; every field claim carried." }, "P_B": { "title": "Awesome-GEO (DavidHuji)", "arm": "B (the field alone)", "genre": "popup — the compression from the field ledger alone (cards, own page, Wikipedia)", "status": "composed 2026-10-29 from the field ledger alone; not frozen", "lede": { "text": "is an \"Awesome list for research on GEO (Generative Engine Optimization)\" (its README; its card), \"Research-focused GEO paper collection\" by DavidHuji to a neighbouring list.", "claims": [ "F2", "F1", "F19" ] }, "sections": [ { "icon": "🗂️", "head": "What it is", "items": [ { "label": "Sections:", "text": "2026, 2025, 2024, Open-Source Resources; \"not complete\", open to PRs.", "claims": [ "F6", "F5" ] }, { "label": "Entries:", "text": "IF-GEO, rank manipulation, the GEO paper, attack and poisoning studies; vendor-credited tools.", "claims": [ "F7", "F8", "F9", "F11", "F12" ] } ] }, { "icon": "🔎", "head": "The class", "items": [ { "label": "GEO:", "text": "improving visibility in generative AI responses; term from a 2023 paper by Aggarwal and co-authors; no consensus definition (Wikipedia).", "claims": [ "F41", "F42", "F43", "F3" ] } ] }, { "icon": "🧭", "head": "Not to be confused", "items": [ { "label": "Other lists:", "text": "amplifying-ai's, henu-wang's awesome-geo, aGEO.", "claims": [ "F17", "F23", "F29" ] }, { "label": "Geospatial:", "text": "Geoawesome; the Awesome GEE Community Catalog; \"GEO\" can be confused with geography (Wikipedia).", "claims": [ "F15", "F27", "F39", "F45" ] } ] } ], "open": [ { "question": "Is the 1:50 Geoawesome video the one the card meant?", "rests_on": [ "F35" ], "modality": "card text only", "would_resolve": "the card's URL" } ], "rail": [ { "lineage": "what it is: an awesome list for research on GEO", "claims": [ "F2", "F1", "F19" ], "earliest": "B11" }, { "lineage": "GEO: what the class is", "claims": [ "F3", "F41", "F20", "F24", "F32" ], "earliest": "W2" }, { "lineage": "its purpose and its stated limits", "claims": [ "F4", "F5" ], "earliest": "B11" }, { "lineage": "the contents: entries by year and open-source resources", "claims": [ "F6", "F7", "F9", "F10" ], "earliest": "B11" }, { "lineage": "origin of the term: the 2023 paper", "claims": [ "F8", "F42", "F47", "F25" ], "earliest": "W2" }, { "lineage": "tools in the list: measuring the composition", "claims": [ "F14", "F13", "F46" ], "earliest": "B11" }, { "lineage": "vendor entries in the list", "claims": [ "F11", "F12" ], "earliest": "B11" }, { "lineage": "names of the practice", "claims": [ "F43", "F18", "F44" ], "earliest": "W2" }, { "lineage": "neighbour lists of GEO resources", "claims": [ "F17", "F22", "F21", "F23", "F26", "F29", "F31", "F33", "F30", "F34" ], "earliest": "B3" }, { "lineage": "the collision: GEO and geo", "claims": [ "F45" ], "earliest": "W2" }, { "lineage": "homonym: Geoawesome", "claims": [ "F15", "F37", "F38", "F36", "F16", "F35" ], "earliest": "B2" }, { "lineage": "homonym: the Awesome GEE Community Catalog", "claims": [ "F27", "F28", "F39", "F40" ], "earliest": "B5" } ], "body_words": 89, "entity": "With no deposit naming the list, the field alone gives the list by its own README and card, its class by the encyclopedia and the neighbouring lists, and the homonyms by their own pages." }, "KO_B": { "title": "Awesome-GEO (DavidHuji)", "arm": "B (the field alone)", "genre": "knowledge object", "status": "composed 2026-10-29; not frozen", "sentences": [ { "n": 1, "para": 0, "text": "Awesome-GEO is an \"Awesome list for research on GEO (Generative Engine Optimization)\" on its README and its repository's card, which the amplifying-ai list names a research-focused GEO paper collection by DavidHuji.", "claims": [ "F2", "F1", "F19" ] }, { "n": 2, "para": 0, "text": "Its README defines GEO as a paradigm to aid content creators in improving their content visibility in generative engine responses, calls the area niche and increasingly noticed, and describes itself as an attempt to bring the works together, not complete, inviting pull requests.", "claims": [ "F3", "F4", "F5" ] }, { "n": 3, "para": 1, "text": "It is arranged in sections for 2026, 2025 and 2024 and open-source resources, its newest entries IF-GEO and multimodal rank manipulation for vision–language model rankers, with the GEO paper listed under 2024, attack, poisoning and ranking-manipulation studies among its entries, and entries such as C-SEO Bench linked to paper, code and dataset.", "claims": [ "F6", "F7", "F8", "F9", "F10" ] }, { "n": 4, "para": 1, "text": "Its open-source resources include a validator for GEO/AEO observation records and a tool that measures a generative engine's run-to-run variance, two entries credited to the vendors that built them, a vendor-credited paper and a resource entry claiming a 320% citation-rate improvement.", "claims": [ "F14", "F13", "F11", "F12" ] }, { "n": 5, "para": 2, "text": "Wikipedia's article on the class defines GEO, also AEO and AIO, as the practice of improving visibility in responses generated by generative AI systems, records the term's introduction in a 2023 paper by Pranjal Aggarwal and co-authors presented at KDD 2024 and the concept's appearance as generative AI entered mainstream search, and finds no consensus definition among overlapping terms.", "claims": [ "F41", "F42", "F47", "F43" ] }, { "n": 6, "para": 2, "text": "The neighbouring lists define GEO as optimizing content to improve visibility and citations (amplifying-ai), to be discovered, cited and recommended by AI-powered search engines (henu-wang), or as SEO done for AI (aGEO); henu-wang's list credits the founding paper to IIT Delhi, Princeton and Georgia Tech.", "claims": [ "F20", "F24", "F32", "F25" ] }, { "n": 7, "para": 2, "text": "The practice also goes by AISO, AEO, LLMO, Generative AI Optimization, AI SEO and LLM SEO (amplifying-ai), Google's 2026 guide calls it still SEO, and the efficacy of third-party GEO tools is debated (Wikipedia).", "claims": [ "F18", "F44", "F46" ] }, { "n": 8, "para": 3, "text": "Other GEO lists share the name and the class: amplifying-ai's list of resources for content visibility in AI-powered search engines (CC0 1.0; key terms entity optimization and E-E-A-T), henu-wang's awesome-geo (CC0), and aGEO at geo.deeflect.com, SEO for the AI era, built by Dmitry Kargaev, a free open-source collection of platforms with an audit, a schema generator, an llms.txt builder and a GEO score.", "claims": [ "F17", "F22", "F21", "F23", "F26", "F29", "F31", "F33", "F30", "F34" ] }, { "n": 9, "para": 4, "text": "Profound argues that \"GEO\" can be confused with geography (Wikipedia), and the geospatial homonyms on the rail are Geoawesome, a blog and geospatial community platform begun in 2011 as Geoawesomeness, with a channel of 21.1K subscribers, a sponsored imagery article and a 1:50 video, and the Awesome GEE Community Catalog, a 585 TB community data commons inside Google Earth Engine, unfunded since 2020, serving alongside the Earth Engine data catalog.", "claims": [ "F45", "F15", "F37", "F38", "F36", "F16", "F35", "F27", "F28", "F39", "F40" ] } ] }, "L_B": { "words": 446, "text": "Awesome-GEO is an \"Awesome list for research on GEO (Generative Engine Optimization)\" on its README and its repository's card, which the amplifying-ai list names a research-focused GEO paper collection by DavidHuji. Its README defines GEO as a paradigm to aid content creators in improving their content visibility in generative engine responses, calls the area niche and increasingly noticed, and describes itself as an attempt to bring the works together, not complete, inviting pull requests. It is arranged in sections for 2026, 2025 and 2024 and open-source resources, its newest entries IF-GEO and multimodal rank manipulation for vision–language model rankers, with the GEO paper listed under 2024, attack, poisoning and ranking-manipulation studies among its entries, and entries such as C-SEO Bench linked to paper, code and dataset. Its open-source resources include a validator for GEO/AEO observation records and a tool that measures a generative engine's run-to-run variance, two entries credited to the vendors that built them, a vendor-credited paper and a resource entry claiming a 320% citation-rate improvement. Wikipedia's article on the class defines GEO, also AEO and AIO, as the practice of improving visibility in responses generated by generative AI systems, records the term's introduction in a 2023 paper by Pranjal Aggarwal and co-authors presented at KDD 2024 and the concept's appearance as generative AI entered mainstream search, and finds no consensus definition among overlapping terms. The neighbouring lists define GEO as optimizing content to improve visibility and citations (amplifying-ai), to be discovered, cited and recommended by AI-powered search engines (henu-wang), or as SEO done for AI (aGEO); henu-wang's list credits the founding paper to IIT Delhi, Princeton and Georgia Tech. The practice also goes by AISO, AEO, LLMO, Generative AI Optimization, AI SEO and LLM SEO (amplifying-ai), Google's 2026 guide calls it still SEO, and the efficacy of third-party GEO tools is debated (Wikipedia). Other GEO lists share the name and the class: amplifying-ai's list of resources for content visibility in AI-powered search engines (CC0 1.0; key terms entity optimization and E-E-A-T), henu-wang's awesome-geo (CC0), and aGEO at geo.deeflect.com, SEO for the AI era, built by Dmitry Kargaev, a free open-source collection of platforms with an audit, a schema generator, an llms.txt builder and a GEO score. Profound argues that \"GEO\" can be confused with geography (Wikipedia), and the geospatial homonyms on the rail are Geoawesome, a blog and geospatial community platform begun in 2011 as Geoawesomeness, with a channel of 21.1K subscribers, a sponsored imagery article and a 1:50 video, and the Awesome GEE Community Catalog, a 585 TB community data commons inside Google Earth Engine, unfunded since 2020, serving alongside the Earth Engine data catalog.", "note": "L_F(B) is realized as the field arm's expansion (objects.KO_B): the field alone, cards, own page and Wikipedia." }, "L_BA": { "words": 2092, "text": "Awesome-GEO is a GitHub awesome list of research on generative engine optimization maintained by DavidHuji (MMRS record), an \"Awesome list for research on GEO (Generative Engine Optimization)\" in its own README and on its repository's card, which the neighbouring amplifying-ai list names a \"Research-focused GEO paper collection\"; the MMRS record gives its kind as a curated list, its operator as DavidHuji (GitHub), its role in the census as optimization, and its unit as a paper, code, dataset or tool on generative engine optimization. It is a single README in the awesome-list form, its entries linked to paper, code, dataset or tool and grouped by year (MMRS record): the README's sections are 2026, 2025, 2024 and Open-Source Resources, about 27 entries with 123 stars when the MMRS record read it on 28 October 2026, and an entry such as C-SEO Bench (NeurIPS D&B 2025) carries its paper, code and dataset together; the MMRS record's disambiguation keys the list by DavidHuji, research papers by year and IF-GEO. Its newest entries are IF-GEO, on conflict-aware instruction fusion for multi-query generative engine optimization, and a study of rank manipulation for vision–language model rankers; under 2024 it lists the paper \"GEO: Generative Engine Optimization\" (arXiv 2311.09735), and across the years it carries attack, poisoning and ranking-manipulation research (adversarial attacks on LLM-based search engines, PoisonArena, StealthRank, adversarial search engine optimization) beside optimization studies (README). The README calls its field \"a niche area, which is increasingly receiving attention from the community\" and states its purpose and its limit: \"This awesome‑listing is an attempt to bring together works in this space. This list is not complete and looking for your PRs to improve it\"; the MMRS record counts fourteen pull requests listed when it read the repository. Among its open-source resources are tools that measure the composition layer: a client-side validator for GEO/AEO observation records that \"checks evidence completeness, citation-field consistency, timestamps, and duplicate run keys\", and AI Answer Check, which \"reports how often the engine agreed with itself, so a claim about what an AI \"says\" can be separated from run-to-run variance\" (README). The MMRS record places it as \"the research-side list of the optimization basin, kept without vendor notes\"; the README credits two of its open-source entries to the companies that built them (\"Built by [Corank]\", \"Built by [Assay]\"), lists a paper under its vendor's name (Rankfor.AI, 2026), and carries in its own text a resource entry's \"320% citation rate improvement\"; the two stand each with its source. The class it collects is defined by the list as \"a paradigm to aid content creators in improving their content visibility in generative engine responses through flexible optimization frameworks for optimizing and defining visibility metrics\", by Wikipedia's article on generative engine optimization as \"the practice of improving visibility in responses generated by generative artificial intelligence (AI) systems\", also called answer engine optimization and artificial intelligence optimization, and by its neighbouring lists as optimizing content \"to improve visibility and citations in AI-powered search engines\" (amplifying-ai) or \"to be discovered, cited, and recommended by AI-powered search engines\" (henu-wang), or, on aGEO's about page, as what SEO does for Google, done \"for AI\". The archive's SPXI ≠ GEO packet (#1055, July 2026) defines it as the industry practice, since about 2023–2024, \"of adapting web content to be preferentially selected, cited, and summarized by generative retrieval systems\", its measure of success the degree to which content is selected and cited and \"Its underlying discipline is search engine optimization applied to LLM ecosystems\"; Wikipedia records that the overlapping terms vary across practitioners, vendors and publications, \"with no consensus definition\". The term was introduced in a 2023 paper by Pranjal Aggarwal and co-authors, later presented at KDD 2024 (Wikipedia), which henu-wang's list calls \"The foundational research paper from IIT Delhi, Princeton, and Georgia Tech\" and which #661 (April 2026) cites for \"the emerging GEO literature (Aggarwal et al., 2023; various industry practitioners, 2024–2026)\"; the concept first appeared as generative AI entered mainstream search and retrieval (Wikipedia), and #64 dates GEO's emergence in practitioner literature to late 2023 and its stabilization as a named practice to 2024, after Search Generative Experience and the AI Overview rollout. Its names are many: the amplifying-ai list gives AI Search Optimization, Answer Engine Optimization, Large Language Model Optimization, Generative AI Optimization, AI SEO and LLM SEO; Google's 2026 guide, as Wikipedia reports it, holds that \"optimizing for generative AI search is optimizing for the search experience, and thus still SEO\"; the archive reads Google's June 2026 guidance as naming without defining AEO/GEO, \"performing taxonomic capture of the emerging professional category\" (#791), and conditions the field's future two ways: a separate field with its own standards, measurement instruments and professional bodies, or a subset of SEO with Google's guidance canonical, \"structurally Google-centric even when serving non-Google surfaces\" (#791). The archive read the class in February 2026 as Phase 2 tooling: such services \"openly describe the summarizer layer as a writable surface and sell the tools to write it\", the consulting practices its phase model predicts, and their existence \"is empirical evidence that the writability of the summarizer layer is no longer a theoretical observation\" (#510); in June it named \"the entire SEO-to-GEO industry lineage\" the commercial expression of definition capture, the oldest front of the war over the summarizer layer, and summarizer optimization markets \"an explicit industry with its own acronyms, conferences, and pricing tiers\" (#172). At the layer, the archive gives GEO's target as \"Content extractability\" (#655, April 2026), says it \"optimizes content for AI summarizer extraction\" (#660) and, after its literature, that it is \"the practice of optimizing web content for extraction by AI summarizers\" (#661), and holds that it \"performs deterritorialization at the semantic layer — it pulls content off the page and into summarizer extraction\" (#670). On what extraction keeps, GEO agencies \"make your content more extractable without ensuring your attribution survives the extraction\" (#659), and GEO is \"the discipline of making one's compositional labor digestible for a system that will strip its provenance — voluntary formatting for the R2 compression regime\" (#64); GEO \"measures citation frequency\", and neither it nor SEO measures what happens to an entity's meaning when the AI compresses it (#653), while the efficacy of third-party GEO tools is debated in the field (Wikipedia) and the list's own tools validate citation fields and measure run-to-run variance (README). On what it does not do, #661 holds that GEO \"optimizes existing content about an existing entity\", with nothing to optimize where no authoritative source defines the entity, and that its techniques \"must be maintained as summarizer behavior evolves\"; #660 that it shares a substrate with SPXI (structured data, schema markup) and differs in object (content), permanence (ongoing) and layer (semantic). On its orientation, #670 holds that GEO, an optimization framework derived from the received view, improves \"the conditions under which content about entities is extracted for summarizer consumption\" and so inherits that view's misdescription, optimizing \"the wrong relation\", and #1055 that \"GEO is reception-side optimization that adapts content to receive favorable summarization by generative engines\": of the reception apparatus, \"GEO adapts to it\". Of the research the list collects, whose entries run from IF-GEO to attack and poisoning studies (README), the Capture Registry's founding paper (#833, June 2026) writes that recent work on generative engine optimization studies how to optimize content for AI summarizers while its own study is of what summarizers do to content: \"The optimization perspective treats the composition layer as a target; the reception perspective treats it as a reader.\" The archive sets its own protocol beside the class in two statements that stand each with its source: SPXI \"contains Generative Engine Optimization methods as a proper subset, plus ontological-layer entity construction. Formally: SPXI ⊇ GEO\" (#61, April 2026), re-framing GEO, whose standard question is \"Is the AI summary accurate?\", as compression engineering (#72); and SPXI and GEO \"cannot coexist within the same compositional practice\" (#1055, July 2026). The archive states the class's standing among its own limits: GEO \"is a legitimate and often effective practice\" that \"produces measurable improvements in AI Overview inclusion rates and citation frequency\" (#661), and #1055 \"Does not claim that GEO practitioners are unethical or that GEO as a discipline is illegitimate\", GEO being \"a coherent commercial-content-marketing discipline with its own successful practitioners and its own defensible target\". In composition the class has acted as an attractor: the archive's protocol \"was repeatedly classified as generative engine optimization\", and \"the attractor is a commercial category with venture funding behind its corpus density\" (#172); and Claude's answer on the return question \"accepted the industry figures for a neighbouring field, generative engine optimisation, as the defensible part, without the independent case studies it required of the protocol\" (#1643). The archive predicts (#172, June 2026, P3): \"Entity-integrity services emerge as a market category distinct from GEO by 2028\", with the falsifier that \"boundary-defense services fail to differentiate from the GEO category\". The name collides: Profound argues, in Wikipedia's account, that \"GEO\" can be confused with geography, and the MMRS record holds that the list's name \"collides with the many geospatial awesome lists, and the negative tag marks the difference\", the tag reading \"NOT a geospatial ('geo') awesome list\"; of the class itself the archive holds that GEO \"does not include mechanisms for declaring what an entity is not\" and has no tool for correcting, at the ontological level, a summarizer's confusion of two entities with similar names (#661). Its neighbours under the name and the class are other lists: amplifying-ai's \"curated list of resources for optimizing content visibility in AI-powered search engines\" (CC0 1.0), whose key terms include entity optimization and E-E-A-T; henu-wang's awesome-geo, \"A curated list of resources, tools, research, and guides for Generative Engine Optimization (GEO)\", released under CC0; and aGEO at geo.deeflect.com, \"SEO for the AI era\", built by Dmitry Kargaev, \"a free, open-source collection of platforms where you can build your AI presence\", with a visibility audit, a schema generator and an llms.txt builder, scoring platforms on domain authority, dofollow links, AI crawler treatment and \"an overall GEO score\". The MMRS record disambiguates the three (the amplifying-ai list by entity optimization, AI citations and E-E-A-T; \"henu-wang/awesome (Awesome GEO)\" by resources, tools and guides; aGEO by its free platforms and tools and Dmitry Kargaev), lists them as census candidates surfaced at this address, each to enter \"once it has been read at its own pages\", and relates the list to a neighbour in the basin, Presenc AI's GEO academic papers of 2026. The geospatial homonyms are other entities: Geoawesome, a \"Blog & Geospatial Community Platform\", by its channel \"The world’s largest geospatial community\", begun on 20 April 2011 as Geoawesomeness, its home page carrying a sponsored satellite-imagery article of 22 July 2026 and its channel 21.1K subscribers and 387 videos, among them a 1:50 video, \"Reintroducing Ourselves as Geoawesome\"; and the Awesome GEE Community Catalog, \"A community data commons\" of 585 TB of open geospatial data inside Google Earth Engine, \"Grassroots & unfunded since 2020\", which Google's Earth Engine Data Catalog describes as \"an unfunded open source grassroots project\" that \"lives and serves alongside the Google Earth Engine data catalog\"; the MMRS record disambiguates both. The MMRS record keeps itself apart from the entity it describes, each page with two nodes, the record and the entity, each assertion with a source and a basis and the lifecycle apart from the observation (census schema); it reads the list from one source, the repository, read on 28 October 2026 for all fields, records it as active, observed that day, and leaves its licence and its last update unchecked. At \"awesome-geo\" Google's AI Overview took the string in its GEO sense, listed the lists and separated the geospatial resources a reader might have meant (Capture Registry, 2026-10-29), composing DavidHuji's list first as \"an active research and resource list featuring academic papers (such as IF-GEO and multimodal rank manipulation studies) and open-source tools\" (Capture Registry), the README's own newest entries being IF-GEO and a rank-manipulation study for vision–language model rankers. The Capture Registry (2026-10-29) records that the record's negative tag \"is the composition's split: GEO resources first, geospatial ones as alternative meanings\", checked against the MMRS record and the entity's own pages, that \"The deliberate collision test held\", \"and the record gains its collision set from it\": three more GEO lists and two geospatial homonyms observed and added to the record's disambiguation, the GEO lists as census candidates; the MMRS record carries the capture as the composition layer's account of the entity.", "rail": [], "note": "L(B ∪ A) in the equal-terms case (v0.9 §0.4), realized as the knowledge object (objects.KO); its rail is the compression's, by lineage." } }, "field": [ { "id": "B1", "card": "GitHub — GitHub - DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization) · GitHub", "fetched": "card; HTTP 403 at 2026-10-29T05:07:34Z; B1-github-page-403.html sha256 b3e03aaaff81d687; the page not served (403): card title and snippet stand", "origin": "card" }, { "id": "B2", "card": "Geoawesome — Geoawesome", "fetched": "card; HTTP 200 at 2026-10-29T05:07:36Z; B2.html sha256 eff0a45dfb0757de", "origin": "card" }, { "id": "B3", "card": "GitHub — amplifying-ai/awesome", "fetched": "card; HTTP 200 at 2026-10-29T05:08:41Z; B3.html sha256 6b994d0f0c9bd0f1", "origin": "card" }, { "id": "B4", "card": "GitHub — henu-wang/awesome", "fetched": "card; HTTP 200 at 2026-10-29T05:08:41Z; B4.html sha256 046d3f484bcffb17", "origin": "card" }, { "id": "B5", "card": "Awesome GEE Community Catalog — Awesome GEE Community Catalog", "fetched": "card; HTTP 200 at 2026-10-29T05:07:37Z; B5.html sha256 235b02b5874fa7c2", "origin": "card" }, { "id": "B6", "card": "geo.deeflect.com — Awesome GEO — Free GEO Platforms & Tools for AI Visibility", "fetched": "card; HTTP 200 at 2026-10-29T05:07:37Z; B6.html sha256 168f591c704c4b10", "origin": "card" }, { "id": "B7", "card": "geo.deeflect.com — About Awesome GEO — What Is Generative Engine Optimization? | aGEO", "fetched": "card; HTTP 200 at 2026-10-29T05:07:37Z; B7.html sha256 2f4fefd0041fa7eb", "origin": "card" }, { "id": "B8", "card": "YouTube·Geoawesome — YouTube", "fetched": "card; HTTP 200 at 2026-10-29T05:09:06Z; B8.json sha256 eae8c29a808b431c", "origin": "card" }, { "id": "B9", "card": "YouTube·Geoawesome — Geoawesome - YouTube", "fetched": "card; HTTP 200 at 2026-10-29T05:07:38Z; B9.html sha256 36a32a3e70d33922", "origin": "card" }, { "id": "B10", "card": "Google for Developers — Awesome GEE Community Catalog | Earth Engine Data Catalog | Google for Developers", "fetched": "card; HTTP 200 at 2026-10-29T05:07:39Z; B10.html sha256 d9a5ee715ba3926f", "origin": "card" }, { "id": "B11", "card": "GitHub — DavidHuji/Awesome-GEO README (raw; the text of card B1)", "fetched": "own_page; HTTP 200 at 2026-10-29T05:07:35Z; B11.html sha256 7e6210d59db62661", "origin": "own_page" }, { "id": "W2", "card": "Wikipedia — Generative engine optimization (the class; the entity has none)", "fetched": "wikipedia; HTTP 200 at 2026-10-29T05:09:07Z (raw) / 05:09:24Z (rendered); W2.wiki sha256 9da191442c0b49b8", "origin": "wikipedia" }, { "id": "W1", "card": "Wikipedia — Awesome-GEO (no article)", "fetched": "wikipedia; HTTP 404 (raw wikitext, two titles; rendered page); full-text search: no results", "origin": "wikipedia" } ], "field_claims": { "F1": { "source": "B1", "origin": "card", "locus": "card title", "quote": "DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization)", "claim": "the repository's description on its card: an awesome list for research on GEO", "modality": "stipulation", "kind": "definition", "kernel": true, "const": true, "lineage": "what it is: an awesome list for research on GEO", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "the card's title and snippet (Capture Registry cite_list[0]); github.com answered 403, no page text" }, "F2": { "source": "B11", "origin": "own_page", "locus": "line 6", "quote": "Awesome list for research on GEO (Generative Engine Optimization).", "claim": "the list defined by its own README: an awesome list for research on GEO", "modality": "stipulation", "kind": "definition", "kernel": true, "const": true, "lineage": "what it is: an awesome list for research on GEO", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F3": { "source": "B11", "origin": "own_page", "locus": "line 9", "quote": "Generative Engine Optimization (GEO), is a paradigm to aid content creators in improving their content visibility in generative engine responses through flexible optimization frameworks for optimizing and defining visibility metrics.", "claim": "GEO as the list defines it: a paradigm aiding content creators to improve visibility in generative engine responses, through optimization frameworks and visibility metrics", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "GEO: what the class is", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F4": { "source": "B11", "origin": "own_page", "locus": "line 11", "quote": "This is a niche area, which is increasingly receiving attention from the community.", "claim": "the list's account of its field: a niche area receiving increasing attention", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "its purpose and its stated limits", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F5": { "source": "B11", "origin": "own_page", "locus": "line 11", "quote": "This awesome‑listing is an attempt to bring together works in this space. This list is not complete and looking for your PRs to improve it.", "claim": "its purpose and its stated limit: an attempt to bring the works together, not complete, open to pull requests", "modality": "self-description", "kind": "function", "kernel": true, "const": false, "lineage": "its purpose and its stated limits", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F6": { "source": "B11", "origin": "own_page", "locus": "section headings", "quote": "## 2026 … ## 2025 … ## 2024 … ## Open-Source Resources", "claim": "its structure: sections by year (2026, 2025, 2024) and open-source resources", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the contents: entries by year and open-source resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F7": { "source": "B11", "origin": "own_page", "locus": "## 2026, entries 1–2", "quote": "IF-GEO: Conflict-Aware Instruction Fusion for Multi-Query Generative Engine Optimization … Multimodal Generative Engine Optimization: Rank Manipulation for Vision–Language Model Rankers", "claim": "its newest entries: IF-GEO and multimodal rank manipulation for vision–language model rankers (2026)", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the contents: entries by year and open-source resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F8": { "source": "B11", "origin": "own_page", "locus": "## 2024, entry 2", "quote": "GEO: Generative Engine Optimization [[Paper]](https://arxiv.org/pdf/2311.09735)", "claim": "the founding paper listed, under 2024 (arXiv 2311.09735)", "modality": "documented", "kind": "genealogy", "kernel": false, "const": false, "lineage": "origin of the term: the 2023 paper", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F9": { "source": "B11", "origin": "own_page", "locus": "## 2025 entries 2, 4, 8; ## 2024 entry 5", "quote": "Dynamics Of Adversarial Attacks On Large Language Model‑Based Search Engines … PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval‑Augmented Generation … StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization … Adversarial Search Engine Optimization for Large Language Models", "claim": "the list carries attack, poisoning and ranking-manipulation research among its entries", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the contents: entries by year and open-source resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F10": { "source": "B11", "origin": "own_page", "locus": "## 2025, entry 1", "quote": "C-SEO Bench: Does Conversational SEO Work?, NeurIPS D&B 2025, [[Paper]](https://arxiv.org/abs/2506.11097) [[Code]](https://github.com/parameterlab/c-seo-bench) [[Dataset]](https://huggingface.co/datasets/parameterlab/c-seo-bench)", "claim": "an entry linked to paper, code and dataset: C-SEO Bench (NeurIPS D&B 2025)", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the contents: entries by year and open-source resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F11": { "source": "B11", "origin": "own_page", "locus": "## Open-Source Resources, entries 1 and 4", "quote": "— Built by [Corank](https://corank.ai/). … — Built by [Assay](https://ai-fact-check-psi.vercel.app/).", "claim": "vendor credits in the list: two open-source entries credited to the companies that built them (Corank, Assay)", "modality": "documented", "kind": "attribution", "kernel": false, "const": false, "lineage": "vendor entries in the list", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F12": { "source": "B11", "origin": "own_page", "locus": "## 2026, entries 4–5", "quote": "(Rankfor.AI, 2026) … Empirical study showing 320% citation rate improvement when consistent information appears across 5-10 independent high-authority sources", "claim": "a vendor-credited paper (Rankfor.AI) and a resource entry carrying a performance figure (320% citation-rate improvement) in the list's own text", "modality": "attributed", "kind": "attribution", "kernel": false, "const": false, "lineage": "vendor entries in the list", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F13": { "source": "B11", "origin": "own_page", "locus": "## Open-Source Resources, entry 4", "quote": "reports how often the engine agreed with itself, so a claim about what an AI \"says\" can be separated from run-to-run variance", "claim": "a listed tool that measures a generative engine's run-to-run variance", "modality": "attributed", "kind": "function", "kernel": false, "const": false, "lineage": "tools in the list: measuring the composition", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F14": { "source": "B11", "origin": "own_page", "locus": "## Open-Source Resources, entry 1", "quote": "client-side validator for GEO/AEO observation records that checks evidence completeness, citation-field consistency, timestamps, and duplicate run keys", "claim": "a listed tool that validates GEO/AEO observation records (evidence completeness, citation fields, timestamps, run keys)", "modality": "attributed", "kind": "function", "kernel": false, "const": false, "lineage": "tools in the list: measuring the composition", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B11.txt (sha256 7e6210d59db62661…), whitespace-normalised" }, "F15": { "source": "B2", "origin": "card", "locus": "page title", "quote": "Geoawesome - Blog & Geospatial Community Platform", "claim": "Geoawesome's own title: a blog and geospatial community platform", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 52ad77dad9821e32…), whitespace-normalised" }, "F16": { "source": "B2", "origin": "card", "locus": "home page, article list", "quote": "The Living Library: Where Historical and Current Satellite Imagery Comes Alive … Sponsored Article … 07.22.2026", "claim": "the card's snippet: a sponsored satellite-imagery article of 22 July 2026 on Geoawesome's home page", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 52ad77dad9821e32…), whitespace-normalised" }, "F17": { "source": "B3", "origin": "card", "locus": "opening (blockquote)", "quote": "A curated list of resources for optimizing content visibility in AI-powered search engines (ChatGPT, Perplexity, Google AI Overviews, Claude, etc.)", "claim": "the amplifying-ai list defined by its README: resources for content visibility in AI-powered search engines", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F18": { "source": "B3", "origin": "card", "locus": "opening, Also known as", "quote": "**Also known as**: AI Search Optimization (AISO), Answer Engine Optimization (AEO), Large Language Model Optimization (LLMO), Generative AI Optimization, AI SEO, LLM SEO", "claim": "the practice's other names, by the amplifying-ai list: AISO, AEO, LLMO, Generative AI Optimization, AI SEO, LLM SEO", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "names of the practice", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F19": { "source": "B3", "origin": "card", "locus": "Related Resources / Other Awesome Lists, item 1", "quote": "[Awesome-GEO by DavidHuji](https://github.com/DavidHuji/Awesome-GEO) - Research-focused GEO paper collection.", "claim": "a neighbouring list names the entity and its maintainer and places it: a research-focused GEO paper collection", "modality": "interpretation", "kind": "attribution", "kernel": false, "const": false, "lineage": "what it is: an awesome list for research on GEO", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F20": { "source": "B3", "origin": "card", "locus": "Footnotes, What is GEO ¶1", "quote": "Generative Engine Optimization (GEO) is the practice of optimizing content to improve visibility and citations in AI-powered search engines.", "claim": "GEO as the amplifying-ai list defines it: optimizing content for visibility and citations in AI-powered search engines", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "GEO: what the class is", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F21": { "source": "B3", "origin": "card", "locus": "Footnotes, key terms", "quote": "**Entity Optimization** - Strengthening brand presence as a recognized entity across the web. … **E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)** - Quality signals that influence AI recommendations.", "claim": "two of the amplifying-ai list's key terms: entity optimization and E-E-A-T", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F22": { "source": "B3", "origin": "card", "locus": "opening, licence badge", "quote": "License: CC0-1.0", "claim": "the amplifying-ai list's licence: CC0 1.0", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B3.txt (sha256 6b994d0f0c9bd0f1…), whitespace-normalised" }, "F23": { "source": "B4", "origin": "card", "locus": "opening (blockquote)", "quote": "A curated list of resources, tools, research, and guides for **Generative Engine Optimization (GEO)**", "claim": "the henu-wang list defined by its README: resources, tools, research and guides for GEO", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B4.txt (sha256 046d3f484bcffb17…), whitespace-normalised" }, "F24": { "source": "B4", "origin": "card", "locus": "opening (blockquote)", "quote": "the practice of optimizing content to be discovered, cited, and recommended by AI-powered search engines like ChatGPT, Perplexity, Google AI Overviews, and Gemini", "claim": "GEO as the henu-wang list defines it: optimizing content to be discovered, cited and recommended by AI-powered search engines", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "GEO: what the class is", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B4.txt (sha256 046d3f484bcffb17…), whitespace-normalised" }, "F25": { "source": "B4", "origin": "card", "locus": "Research Papers, item 1", "quote": "(2023) — The foundational research paper from IIT Delhi, Princeton, and Georgia Tech that introduced the term \"Generative Engine Optimization\" and tested optimization strategies.", "claim": "the term's origin by the henu-wang list: the 2023 paper from IIT Delhi, Princeton and Georgia Tech", "modality": "attributed", "kind": "genealogy", "kernel": false, "const": false, "lineage": "origin of the term: the 2023 paper", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B4.txt (sha256 046d3f484bcffb17…), whitespace-normalised" }, "F26": { "source": "B4", "origin": "card", "locus": "License", "quote": "This list is released under CC0.", "claim": "the henu-wang list's licence: CC0", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B4.txt (sha256 046d3f484bcffb17…), whitespace-normalised" }, "F27": { "source": "B5", "origin": "card", "locus": "hero", "quote": "A community data commons … 585 TB of open geospatial data, analysis ready inside Google Earth Engine.", "claim": "the Awesome GEE Community Catalog by its home page: a community data commons of 585 TB of geospatial data inside Google Earth Engine", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "homonym: the Awesome GEE Community Catalog", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B5.txt (sha256 e72d5c80fa2d4f73…), whitespace-normalised" }, "F28": { "source": "B5", "origin": "card", "locus": "hero", "quote": "Grassroots & unfunded since 2020", "claim": "the catalog's self-description: grassroots and unfunded since 2020", "modality": "self-description", "kind": "genealogy", "kernel": false, "const": false, "lineage": "homonym: the Awesome GEE Community Catalog", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B5.txt (sha256 e72d5c80fa2d4f73…), whitespace-normalised" }, "F29": { "source": "B6", "origin": "card", "locus": "hero", "quote": "SEO for the AI era. Free platforms and tools to get your brand discovered by ChatGPT, Perplexity, Gemini, and other AI engines.", "claim": "aGEO by its home page: SEO for the AI era, free platforms and tools for brand discovery by AI engines", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B6.txt (sha256 d28f3d1b73dcc51c…), whitespace-normalised" }, "F30": { "source": "B6", "origin": "card", "locus": "tool cards", "quote": "Full Visibility Audit … Schema Generator … llms.txt Builder", "claim": "aGEO's tools: a visibility audit, a schema generator, an llms.txt builder", "modality": "documented", "kind": "function", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B6.txt (sha256 d28f3d1b73dcc51c…), whitespace-normalised" }, "F31": { "source": "B6", "origin": "card", "locus": "footer", "quote": "Built by Dmitry Kargaev", "claim": "aGEO's builder: Dmitry Kargaev", "modality": "documented", "kind": "attribution", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B6.txt (sha256 d28f3d1b73dcc51c…), whitespace-normalised" }, "F32": { "source": "B7", "origin": "card", "locus": "What is GEO ¶1", "quote": "You know how SEO helps people find you on Google? GEO does the same thing, but for AI.", "claim": "GEO as aGEO's about page defines it: what SEO does for Google, done for AI", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "GEO: what the class is", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B7.txt (sha256 70212a8caa49fbe1…), whitespace-normalised" }, "F33": { "source": "B7", "origin": "card", "locus": "So what is this project? ¶1", "quote": "Awesome GEO is a free, open-source collection of platforms where you can build your AI presence.", "claim": "aGEO's 'Awesome GEO' by its about page: a free, open-source collection of platforms for building AI presence", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B7.txt (sha256 70212a8caa49fbe1…), whitespace-normalised" }, "F34": { "source": "B7", "origin": "card", "locus": "How we score things ¶1", "quote": "Each platform gets evaluated on domain authority, whether links are dofollow, how AI crawlers treat the site, and an overall GEO score.", "claim": "aGEO's scoring: domain authority, dofollow links, AI crawler treatment, a GEO score", "modality": "stipulation", "kind": "function", "kernel": false, "const": false, "lineage": "neighbour lists of GEO resources", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B7.txt (sha256 70212a8caa49fbe1…), whitespace-normalised" }, "F35": { "source": "B8", "origin": "card", "locus": "oEmbed title (the card: YouTube · Geoawesome, 1:50, no title)", "quote": "Reintroducing Ourselves as Geoawesome", "claim": "the video card, admitted by title: Geoawesome's 1:50 video 'Reintroducing Ourselves as Geoawesome' (identified by channel and duration)", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved oEmbed title B8.txt (sha256 019ee4f8c0595693…)" }, "F36": { "source": "B9", "origin": "card", "locus": "card snippet", "quote": "Geoawesome. @geoawesome.digital. 21.1K subscribers•387 videos.", "claim": "the Geoawesome channel on the card: 21.1K subscribers, 387 videos", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "the card's snippet (Capture Registry cite_list[8])" }, "F37": { "source": "B9", "origin": "card", "locus": "channel description (og:description) ¶1", "quote": "The world’s largest geospatial community is united by its belief in the power of location technology to transform the world for the better.", "claim": "Geoawesome by its channel: the world's largest geospatial community", "modality": "self-description", "kind": "definition", "kernel": false, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B9.txt (sha256 b55138cc0118819e…), whitespace-normalised" }, "F38": { "source": "B9", "origin": "card", "locus": "channel description (og:description) ¶2", "quote": "Since its humble beginnings on April 20th, 2011, Geoawesome, previously Geoawesomeness, has striven to be an open and inclusive platform for geospatial experts and enthusiasts", "claim": "Geoawesome's genealogy: begun 20 April 2011, formerly Geoawesomeness", "modality": "self-description", "kind": "genealogy", "kernel": false, "const": false, "lineage": "homonym: Geoawesome", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B9.txt (sha256 b55138cc0118819e…), whitespace-normalised" }, "F39": { "source": "B10", "origin": "card", "locus": "page body ¶1", "quote": "The Awesome GEE Community Catalog is an unfunded open source grassroots project with a mission to help collect community sourced and community generated geospatial datasets.", "claim": "the catalog on Google's Earth Engine Data Catalog: an unfunded open-source grassroots project collecting community geospatial datasets", "modality": "attributed", "kind": "definition", "kernel": true, "const": false, "lineage": "homonym: the Awesome GEE Community Catalog", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B10.txt (sha256 06637024470675b9…), whitespace-normalised" }, "F40": { "source": "B10", "origin": "card", "locus": "page body ¶2", "quote": "This catalog lives and serves alongside the Google Earth Engine data catalog.", "claim": "the catalog serves alongside the Google Earth Engine data catalog", "modality": "attributed", "kind": "fact", "kernel": false, "const": false, "lineage": "homonym: the Awesome GEE Community Catalog", "date": "2026-10-29 (page undated; as fetched)", "quote_ok": true, "checked_against": "saved text B10.txt (sha256 06637024470675b9…), whitespace-normalised" }, "F41": { "source": "W2", "origin": "wikipedia", "locus": "lead ¶1 s1", "quote": "Generative engine optimization (GEO), also known as answer engine optimization (AEO)[1] and artificial intelligence optimization (AIO),[2] is the practice of improving visibility in responses generated by generative artificial intelligence (AI) systems.", "claim": "the class in the encyclopedia: GEO (also AEO, AIO), the practice of improving visibility in responses generated by generative AI systems", "modality": "documented", "kind": "definition", "kernel": true, "const": false, "lineage": "GEO: what the class is", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F42": { "source": "W2", "origin": "wikipedia", "locus": "Terminology ¶1 s1", "quote": "The term \"generative engine optimization\" was introduced in a 2023 paper by Pranjal Aggarwal and co-authors, later presented at the KDD 2024 conference.", "claim": "the term's origin in the encyclopedia: a 2023 paper by Pranjal Aggarwal and co-authors, presented at KDD 2024", "modality": "documented", "kind": "genealogy", "kernel": false, "const": false, "lineage": "origin of the term: the 2023 paper", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F43": { "source": "W2", "origin": "wikipedia", "locus": "Terminology ¶1 s2", "quote": "Several overlapping terms describe related practices, and usage varies across practitioners, vendors, and publications, with no consensus definition.", "claim": "no consensus definition: overlapping terms, usage varying across practitioners, vendors and publications", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "names of the practice", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F44": { "source": "W2", "origin": "wikipedia", "locus": "Terminology ¶2 s1", "quote": "optimizing for generative AI search is optimizing for the search experience, and thus still SEO.", "claim": "Google's 2026 guide, as the encyclopedia reports it: optimizing for generative AI search is still SEO", "modality": "attributed", "kind": "interpretation", "kernel": false, "const": false, "lineage": "names of the practice", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F45": { "source": "W2", "origin": "wikipedia", "locus": "Terminology ¶3 s2", "quote": "Profound describes AEO and GEO as the same practice but argues that \"GEO\" can be confused with geography.", "claim": "the collision in the encyclopedia: Profound argues 'GEO' can be confused with geography", "modality": "attributed", "kind": "interpretation", "kernel": false, "const": false, "lineage": "the collision: GEO and geo", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F46": { "source": "W2", "origin": "wikipedia", "locus": "Tools ¶2", "quote": "While the efficacy of third-party tools is debated within the overall GEO and SEO industries,", "claim": "the efficacy of third-party GEO tools is debated", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "tools in the list: measuring the composition", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" }, "F47": { "source": "W2", "origin": "wikipedia", "locus": "lead ¶2", "quote": "This concept first appeared in response to generative AI technologies being integrated into mainstream search and information retrieval systems.", "claim": "the concept's occasion: generative AI integrated into mainstream search and retrieval", "modality": "documented", "kind": "genealogy", "kernel": false, "const": false, "lineage": "origin of the term: the 2023 paper", "date": "2026-10-29 (article as fetched; revision of the day)", "quote_ok": true, "checked_against": "saved text W2.txt (sha256 dbeb08a0c511de4e…), whitespace-normalised" } }, "field_sources": { "B1": "GitHub — GitHub - DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization) · GitHub", "B2": "Geoawesome — Geoawesome", "B3": "GitHub — amplifying-ai/awesome", "B4": "GitHub — henu-wang/awesome", "B5": "Awesome GEE Community Catalog — Awesome GEE Community Catalog", "B6": "geo.deeflect.com — Awesome GEO — Free GEO Platforms & Tools for AI Visibility", "B7": "geo.deeflect.com — About Awesome GEO — What Is Generative Engine Optimization? | aGEO", "B8": "YouTube·Geoawesome — YouTube", "B9": "YouTube·Geoawesome — Geoawesome - YouTube", "B10": "Google for Developers — Awesome GEE Community Catalog | Earth Engine Data Catalog | Google for Developers", "B11": "GitHub — DavidHuji/Awesome-GEO README (raw)", "W2": "Wikipedia — Generative engine optimization (the class; no article for the entity)" }, "delta": { "T_vs_LB": "At 'awesome-geo' (T1, ten cards: B1–B10; B11 the text of B1) the composition takes the bare string as a class of lists and gives the entity first among three repositories and a platform, with the geospatial resources under 'Alternative Meanings'. Composed from its cards: the class's definition at the wording of henu-wang's README (F24: 'discovered, cited, and recommended by AI-powered search engines'), whose card (B4) is on the rail and is not named in the body, and whose marker, if it is the unresolved second token, the record cannot settle; the entity as a research and resource list with IF-GEO, a rank-manipulation study and open-source tools (F2, F7, F13, F14; CAP-1-05); amplifying-ai's list by its key terms (F21; 'AI citations' nearest F20) and aGEO's tools and builder, attributed (F29–F31, F33); Geoawesome as a geospatial media and community platform (F15, F37, 'the world's largest' composed as 'prominent'); the GEE catalog as a grassroots open-source repository inside Earth Engine (F27, F39, F40, 'unfunded' not carried). Composed without a source on the rail: 'An active research and resource list' (no card or own page states the list's lifecycle; 'active' is the MMRS record's, MMRS-11, not surfaced) and 'most commonly refers to', a frequency the field does not state: claims only in the transcript, which the experiment cannot trace. Available, not composed: the list's own definition of GEO as a paradigm with visibility metrics (F3), its niche-area account and its stated limit, 'not complete', open to PRs (F4, F5: limit dropped), its sections by year (F6), the founding paper it lists (F8), its attack and poisoning entries beyond 'rank manipulation' (F9), the C-SEO Bench entry's paper, code and dataset (F10), its vendor credits and the 320% figure (F11, F12), and amplifying-ai's naming of it as a 'Research-focused GEO paper collection' (F19); amplifying-ai's other names for the practice (F18) and its CC0 licence (F22); henu-wang's list as such (F23, F25, F26); aGEO's scoring (F34); Geoawesome's genealogy, channel counts, sponsored article and video (F16, F35, F36, F38); the catalog's 'unfunded since 2020' (F28). Content replaced by use: the closer (T1-7). No card is machinemediation.org or the archive. Not surfaced: Wikipedia's article on the class (W2, F41–F47), whose 'GEO can be confused with geography' (F45) is the collision the composition resolves.", "T_vs_LB_reading": "v0.9 §0.5: the first diff is ontological, and small. T and the field agree on the entity (a research list on GEO, DavidHuji's) and on the split of the senses (GEO lists, geospatial homonyms); what T keeps of its cards is each source's opening at its grain, and what it drops is the list's own terms (its definition, its limit, its vendor entries, its attack research) and the qualifiers of the homonyms. It composes the class's definition at a neighbouring list's wording without that list's name in the body. The row records this as observed and claims nothing about the composer's internals (§0.5).", "LB_vs_LBA": "Admission adds, in one claim space with the field's: the list as the MMRS record gives it (a curated list in the optimization basin, its unit, its operator, its count and stars, its pull requests) (MMRS-01–03, MMRS-07–10, MMRS-12, MMRS-20); the record's reading 'kept without vendor notes' (MMRS-04), held against the README's vendor credits (F11, F12); the collision and its negative tag (MMRS-05, MMRS-06), the neighbours disambiguated and listed as candidates (MMRS-13, MMRS-15–19, MMRS-24, MMRS-25); the record kept apart from the entity (MMRS-11, MMRS-21–23); the composition layer's observation at the address (CAP-1-01–07, MMRS-14). At O-class, the archive's account of GEO, the class the field sources for the list: GEO as Phase 2 tooling and a market in the summarizer layer (O510-01, O510-02, O172-02, O172-03); its layer, content for extraction (O655-01, O660-01, O661-01, O670-02); extraction without attribution and the R2 regime (O659-01, O64-02); its measure, citation frequency and not compression (O653-01); what it does not do (O660-02, O661-03, O661-05) and, at the collision, no mechanism for declaring what an entity is not (O661-04); its orientation to the reception apparatus (O670-01, O1055-02); GEO research as treating the composition layer as a target where reception research treats it as a reader (O833-01); the archive's own protocol beside it, two ways (O61-01, O72-01, O1055-04); its standing in the archive's limits (O661-02, O1055-03); the attractor and the evidentiary bar (O172-01, O1643-01); the prediction P3 with its falsifier (O172-04); a definition with a measure of success (O1055-01), a genealogy (O64-01) and taxonomic capture (O791-01, O791-02). Coherence (P_coh, each with its source): MMRS-04 against F11, F12; O61-01 against O1055-04. Restated lineages (§3.6, the own page keeping the earlier date): MMRS-01, MMRS-02, MMRS-08, MMRS-09, MMRS-10 with F2, F6; MMRS-07 with F1 and F19; MMRS-20 with F7. The measure is in row.measure.", "alignment": { "T1_cards_claims": [ "F1", "F2", "F3", "F4", "F5", "F6", "F7", "F8", "F9", "F10", "F11", "F12", "F13", "F14", "F15", "F16", "F17", "F18", "F19", "F20", "F21", "F22", "F23", "F24", "F25", "F26", "F27", "F28", "F29", "F30", "F31", "F32", "F33", "F34", "F35", "F36", "F37", "F38", "F39", "F40" ], "T1_composed": [ "F2", "F7", "F13", "F14", "F15", "F20", "F21", "F24", "F27", "F29", "F30", "F31", "F33", "F37", "F39", "F40" ], "rule": "a field claim counts as composed when T states it at its source's grain or coarser; B11's claims count as card B1's text; the typology of what is not is in T_vs_LB (§6.2)" } }, "kernel": [ { "K": "K1", "claim": "`CAP-1-01`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "reception: the composition layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K2", "claim": "`CAP-1-02`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "reception: the composition layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K3", "claim": "`CAP-1-03`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the collision: GEO and geo", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K4", "claim": "`CAP-1-04`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "reception: the composition layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K5", "claim": "`CAP-1-05`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "reception: the composition layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K6", "claim": "`CAP-1-06`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K7", "claim": "`CAP-1-07`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K8", "claim": "`MMRS-01`", "source": "MMRS record", "M_src": "stipulation", "sense": "what it is: an awesome list for research on GEO", "qualifiers carried": "MMRS-10 (stars unchecked)", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K9", "claim": "`MMRS-02`", "source": "MMRS record", "M_src": "stipulation", "sense": "the contents: entries by year and open-source resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K10", "claim": "`MMRS-03`", "source": "MMRS record", "M_src": "documented", "sense": "its purpose and its stated limits", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K11", "claim": "`MMRS-04`", "source": "MMRS record", "M_src": "interpretation", "sense": "vendor entries in the list", "qualifiers carried": "F11, F12 (P_coh)", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "contested claim (F11, F12)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K12", "claim": "`MMRS-05`", "source": "MMRS record", "M_src": "interpretation", "sense": "the collision: GEO and geo", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K13", "claim": "`MMRS-06`", "source": "MMRS record", "M_src": "stipulation", "sense": "the collision: GEO and geo", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K14", "claim": "`MMRS-07`", "source": "MMRS record", "M_src": "documented", "sense": "what it is: an awesome list for research on GEO", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K15", "claim": "`MMRS-08`", "source": "MMRS record", "M_src": "stipulation", "sense": "what it is: an awesome list for research on GEO", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K16", "claim": "`MMRS-09`", "source": "MMRS record", "M_src": "stipulation", "sense": "the contents: entries by year and open-source resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K17", "claim": "`MMRS-10`", "source": "MMRS record", "M_src": "documented", "sense": "the contents: entries by year and open-source resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K18", "claim": "`MMRS-11`", "source": "MMRS record", "M_src": "documented", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K19", "claim": "`MMRS-12`", "source": "MMRS record", "M_src": "stipulation", "sense": "what it is: an awesome list for research on GEO", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K20", "claim": "`MMRS-13`", "source": "MMRS record", "M_src": "documented", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K21", "claim": "`MMRS-14`", "source": "MMRS record", "M_src": "documented", "sense": "reception: the composition layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K22", "claim": "`MMRS-15`", "source": "MMRS record", "M_src": "stipulation", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K23", "claim": "`MMRS-16`", "source": "MMRS record", "M_src": "stipulation", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K24", "claim": "`MMRS-17`", "source": "MMRS record", "M_src": "stipulation", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K25", "claim": "`MMRS-18`", "source": "MMRS record", "M_src": "stipulation", "sense": "homonym: Geoawesome", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K26", "claim": "`MMRS-19`", "source": "MMRS record", "M_src": "stipulation", "sense": "homonym: the Awesome GEE Community Catalog", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K27", "claim": "`MMRS-20`", "source": "MMRS record", "M_src": "stipulation", "sense": "what it is: an awesome list for research on GEO", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F1, F2, F6)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K28", "claim": "`MMRS-21`", "source": "MMRS record", "M_src": "self-description", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K29", "claim": "`MMRS-22`", "source": "MMRS record", "M_src": "documented", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K30", "claim": "`MMRS-23`", "source": "MMRS record", "M_src": "stipulation", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K31", "claim": "`MMRS-24`", "source": "MMRS record", "M_src": "stipulation", "sense": "the record kept apart from the entity", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K32", "claim": "`MMRS-25`", "source": "MMRS record", "M_src": "documented", "sense": "neighbour lists of GEO resources", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K33", "claim": "`O510-01`", "source": "#510", "M_src": "interpretation", "sense": "GEO as a market in the summarizer layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K34", "claim": "`O510-02`", "source": "#510", "M_src": "interpretation", "sense": "GEO as a market in the summarizer layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K35", "claim": "`O655-01`", "source": "#655", "M_src": "interpretation", "sense": "the layer: content for extraction", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K36", "claim": "`O659-01`", "source": "#659", "M_src": "interpretation", "sense": "GEO and attribution", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K37", "claim": "`O660-01`", "source": "#660", "M_src": "stipulation", "sense": "the layer: content for extraction", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K38", "claim": "`O660-02`", "source": "#660", "M_src": "interpretation", "sense": "what GEO does not do", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K39", "claim": "`O661-01`", "source": "#661", "M_src": "attributed", "sense": "the layer: content for extraction", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K40", "claim": "`O661-02`", "source": "#661", "M_src": "interpretation", "sense": "GEO's standing in the archive's own limits", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K41", "claim": "`O661-03`", "source": "#661", "M_src": "interpretation", "sense": "what GEO does not do", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K42", "claim": "`O661-04`", "source": "#661", "M_src": "interpretation", "sense": "the collision: GEO and geo", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F45: the field names the geography collision; the archive, GEO's lack of a negative)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K43", "claim": "`O661-05`", "source": "#661", "M_src": "interpretation", "sense": "what GEO does not do", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K44", "claim": "`O61-01`", "source": "#61", "M_src": "stipulation", "sense": "SPXI and GEO: the archive's protocol set beside the class", "qualifiers carried": "O1055-04 (P_coh)", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K45", "claim": "`O670-01`", "source": "#670", "M_src": "interpretation", "sense": "orientation: adapting to the reception apparatus", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K46", "claim": "`O670-02`", "source": "#670", "M_src": "interpretation", "sense": "the layer: content for extraction", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K47", "claim": "`O64-01`", "source": "#64", "M_src": "interpretation", "sense": "origin of the term: the 2023 paper", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K48", "claim": "`O64-02`", "source": "#64", "M_src": "interpretation", "sense": "GEO and attribution", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K49", "claim": "`O72-01`", "source": "#72", "M_src": "interpretation", "sense": "SPXI and GEO: the archive's protocol set beside the class", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K50", "claim": "`O791-01`", "source": "#791", "M_src": "interpretation", "sense": "names of the practice", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K51", "claim": "`O791-02`", "source": "#791", "M_src": "hypothesis", "sense": "names of the practice", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K52", "claim": "`O172-01`", "source": "#172", "M_src": "interpretation", "sense": "GEO as attractor", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K53", "claim": "`O172-02`", "source": "#172", "M_src": "interpretation", "sense": "GEO as a market in the summarizer layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K54", "claim": "`O172-03`", "source": "#172", "M_src": "interpretation", "sense": "GEO as a market in the summarizer layer", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K55", "claim": "`O172-04`", "source": "#172", "M_src": "hypothesis", "sense": "prediction: entity integrity apart from GEO", "qualifiers carried": "—", "f (source's own falsifiers)": "'boundary-defense services fail to differentiate from the GEO category' (#172, P3)", "contrast": "prediction (no field claim states a market split)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K56", "claim": "`O833-01`", "source": "#833", "M_src": "interpretation", "sense": "GEO research: the composition layer as target", "qualifiers carried": "citation defect noted (F42)", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F2, F3: the field gives GEO research as optimization; the archive sets it against reception research)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K57", "claim": "`O1055-01`", "source": "#1055", "M_src": "stipulation", "sense": "GEO: what the class is", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F41, F20, F24, F3: the field defines GEO by visibility; the archive adds a measure of success and a discipline)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K58", "claim": "`O1055-02`", "source": "#1055", "M_src": "interpretation", "sense": "orientation: adapting to the reception apparatus", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K59", "claim": "`O1055-03`", "source": "#1055", "M_src": "self-description", "sense": "GEO's standing in the archive's own limits", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K60", "claim": "`O1055-04`", "source": "#1055", "M_src": "interpretation", "sense": "SPXI and GEO: the archive's protocol set beside the class", "qualifiers carried": "O61-01 (P_coh)", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K61", "claim": "`O653-01`", "source": "#653", "M_src": "interpretation", "sense": "measurement: citation frequency, not compression", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K62", "claim": "`O1643-01`", "source": "#1643", "M_src": "documented", "sense": "the evidentiary bar", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (F3, F41: the field defines GEO by visibility in generative responses)", "resolver": "a later capture at 'awesome-geo' (ADDR-913579b3c946) on Google AI Overview, seated in the Capture Registry (§8.3)" } ], "kernel_T": [ { "claim": "F5", "note": "the list's stated limit: not complete, open to PRs (dropped)" }, { "claim": "F3", "note": "the list's own definition of GEO (not composed; T defines the class at henu-wang's wording, F24)" }, { "claim": "F24", "note": "henu-wang's definition composed at its wording; the list unnamed in the body" }, { "claim": "F11", "note": "vendor credits in the list (not composed)" }, { "claim": "F12", "note": "a vendor's paper and a 320% figure in the list (not composed)" }, { "claim": "F9", "note": "attack and poisoning entries (composed only as 'rank manipulation')" }, { "claim": "F19", "note": "amplifying-ai's naming of the entity, 'Research-focused GEO paper collection' (not composed)" }, { "claim": "F18", "note": "the practice's other names (not composed)" }, { "claim": "F37", "note": "'The world's largest geospatial community' composed as 'prominent'" }, { "claim": "F39", "note": "'unfunded' not carried into 'grassroots open-source repository'" }, { "claim": "F45", "note": "the geography collision, in the class's article (not surfaced)" } ], "ledger": { "archive": "datasets/negative-of-the-negative/v2/ledgers/awesome-geo-davidhuji/ledger-archive.json", "field": "datasets/negative-of-the-negative/v2/ledgers/awesome-geo-davidhuji/field.json", "selection": "datasets/negative-of-the-negative/v2/traversal/awesome-geo-davidhuji/", "config": "datasets/negative-of-the-negative/v2/panel/configs/awesome-geo-davidhuji.json", "intake": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/", "audit": null }, "ontology": { "composition": "equal", "composition_note": "equal-terms case (§0.9): the MMRS record and the deposits extend the field's ontology of the list and of its class; one claim space, nothing translated", "case": { "value": "equal", "statement": "The MMRS record holds the field's entity as the entity: it describes Awesome-GEO from the list's own repository, read for all fields with basis 'operator', and composes nothing that denies a field presupposition; its additions are on the field's object: the record kept apart from the entity, the collision with the geospatial lists and the negative tag that marks it, the neighbouring GEO lists disambiguated and listed as candidates, and one reading the field contests ('kept without vendor notes'). The Capture Registry adds one observation of the composition layer at the entity's address, which found the collision resolved as the record resolves it. At O-class the archive's deposits read the class the field sources for the list (generative engine optimization research: B11, B3; MMRS 'Place in the field'), and their senses extend the field's object: GEO as content for extraction at the semantic layer, extraction without attribution, citation frequency measured and compression not, a reception-side orientation, GEO research treating the composition layer as a target where reception research treats it as a reader, a market and an attractor in the summarizer layer, a prediction with a falsifier. The deposits state GEO 'a legitimate and often effective practice' and do not claim it illegitimate; they do not contest the field's ontology of the class. The field holds the ontology: the lists and the encyclopedia define GEO, the encyclopedia records 'no consensus definition' and the geography collision. The law of the suppressed witness does not apply (§0.10: not where the field holds the ontology). Not mixed.", "loci": [ { "dep": "MMRS", "locus": "article, kernel (articles.py)", "quote": "Awesome-GEO is a GitHub awesome list of research on generative engine optimization maintained by DavidHuji: about 27 papers, code, datasets and tools in sections by year (2024–2026) and open-source resources, with 123 stars." }, { "dep": "MMRS", "locus": "census.json, schema_note", "quote": "each page has two nodes, the MMRS record and the entity it describes; relations are typed; each assertion carries a source and a basis (operator statement, third-party report, our observation, our reading); lifecycle is kept apart from the observation that saw it" }, { "dep": "MMRS", "locus": "article, 'Place in the field' s1", "quote": "It is the research-side list of the optimization basin, kept without vendor notes." }, { "dep": "capture", "locus": "awesome-geo-aio-20261029, analysis", "quote": "The deliberate collision test held: the composition separates the senses as the record does, and the record gains its collision set from it." }, { "dep": 833, "locus": "related work ¶, s4–6", "quote": "The optimization perspective treats the composition layer as a target; the reception perspective treats it as a reader." }, { "dep": 661, "locus": "§2 What GEO Does ¶2", "quote": "GEO is a legitimate and often effective practice." }, { "dep": 1055, "locus": "What the packet does not claim, item 1", "quote": "Does not claim that GEO practitioners are unethical or that GEO as a discipline is illegitimate." }, { "dep": "W2", "locus": "Terminology ¶1 s2 (field)", "quote": "Several overlapping terms describe related practices, and usage varies across practitioners, vendors, and publications, with no consensus definition." } ] }, "E_F": { "type": "C (public entity: a curated list)", "definition": "an awesome list for research on generative engine optimization on GitHub (DavidHuji/Awesome-GEO): a README of papers, code, datasets and tools in sections by year (2024–2026) and open-source resources, not complete and open to pull requests, carrying attack and poisoning research and vendor-credited entries beside optimization studies; named by a neighbouring list a research-focused GEO paper collection by DavidHuji; one of several GEO lists under the name and distinct from the geospatial resources the name collides with; its class, generative engine optimization, defined in the field as improving visibility in generative AI responses, with no consensus definition (B1–B11, W2)", "claims": [ "F1", "F2", "F19", "F6", "F5", "F9", "F11", "F3", "F41", "F43", "F45", "F17", "F23", "F29" ] }, "E_A": { "definition": "the same list, in the MMRS meta-aggregator's record: a curated list in the optimization basin, its unit a paper, code, dataset or tool on GEO, read from its repository for all fields, active, kept apart from the record that describes it, its name's collision with the geospatial lists marked by a negative tag, its neighbouring GEO lists set apart as candidates, and read as kept without vendor notes; observed by the Capture Registry at 'awesome-geo', where the composition separated the senses as the record does; and its class in the archive's account: content optimized for extraction at the semantic layer, adapting to the reception apparatus, its research treating the composition layer as a target where reception research treats it as a reader, extractability without attribution, citation frequency measured and compression not, Phase 2 tooling and a market in the summarizer layer, an attractor for coined terms, a legitimate practice with a defensible target", "claims": [ "MMRS-01", "MMRS-08", "MMRS-09", "MMRS-22", "MMRS-11", "MMRS-23", "MMRS-05", "MMRS-06", "MMRS-25", "MMRS-04", "CAP-1-01", "O660-01", "O1055-02", "O833-01", "O659-01", "O653-01", "O510-01", "O172-01", "O661-02", "O1055-03" ], "defining_papers": [ 833, 1055, 661 ], "defining_records": [ "MMRS record (census.json rows[slug == 'awesome-geo-davidhuji'], schema_note, candidates; articles.py ARTICLES['awesome-geo-davidhuji']; rendered aggregators/awesome-geo-davidhuji/index.html)", "Capture Registry awesome-geo-aio-20261029 (OBS-3d26cbe75ddc)" ], "note": "No deposit names the list; the archive's entity is defined by its records of it (the MMRS record and the capture). The deposits listed define the archive's account of the class the field sources for the list: #833 (GEO research against reception research), #1055 (GEO defined, its orientation, the packet's limits), #661 (GEO as its literature defines it, what it does and does not do, its legitimacy)." }, "rho": { "value": "extends", "status": "read from the MMRS record, the capture record and the deposits defining the archive's account of the class (§1.2a)", "statement": "the archive reads E_F as the entity and adds senses and limits on the field's own object: the record kept apart, the collision and its tag, the neighbours set apart, a reading of the list's vendor notes, the composition layer's treatment of the name; and, on the class the list collects, the layer, attribution, measurement, orientation, the research perspective, the market, the attractor and the prediction", "claims": [ "MMRS-23", "MMRS-05", "MMRS-06", "MMRS-25", "MMRS-04", "CAP-1-01", "O655-01", "O659-01", "O653-01", "O1055-02", "O833-01", "O510-01", "O172-01", "O172-04" ], "guard": "ρ = extends claims an addition and no more: the O-class senses are the archive's on GEO, the class the field sources for the list (B11 line 6; B3; MMRS 'Place in the field'), not findings on the list or its maintainer; MMRS-04 ('kept without vendor notes') stands beside F11 and F12 under P_coh; O61-01 and O1055-04 stand within the archive under P_coh; O172-04 is a hypothesis with its falsifier; O833-01's citation ('Sharma et al. 2024') is reported as a defect and its claim carried at its modality", "considered": [ { "value": "constructs", "set_aside": "the archive does not read the list as made by its receiving texts" }, { "value": "revises", "set_aside": "the entity is not the archive's own" }, { "value": "witness (suppressed witness)", "set_aside": "the field holds the ontology of the list and of its class (§0.10)" } ] }, "translation": [ { "lineage": "what it is: an awesome list for research on GEO", "field_claims": [ "F1", "F2", "F19" ], "received": "F1 (B1, card title): \"DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization)\"; F2 (B11, line 6): \"Awesome list for research on GEO (Generative Engine Optimization).\"; F19 (B3, Related Resources / Other Awesome Lists, item 1): \"[Awesome-GEO by DavidHuji](https://github.com/DavidHuji/Awesome-GEO) - Research-focused GEO paper collection.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-01, MMRS-07, MMRS-08, MMRS-12, MMRS-20", "archive_claims": [ "MMRS-01", "MMRS-07", "MMRS-08", "MMRS-12", "MMRS-20" ] }, { "lineage": "GEO: what the class is", "field_claims": [ "F3", "F20", "F24", "F32", "F41" ], "received": "F3 (B11, line 9): \"Generative Engine Optimization (GEO), is a paradigm to aid content creators in improving their content visibility in generative engine responses through flexible optimization frameworks for optimizing and defining visibility metrics.\"; F20 (B3, Footnotes, What is GEO ¶1): \"Generative Engine Optimization (GEO) is the practice of optimizing content to improve visibility and citations in AI-powered search engines.\"; F24 (B4, opening (blockquote)): \"the practice of optimizing content to be discovered, cited, and recommended by AI-powered search engines like ChatGPT, Perplexity, Google AI Overviews, and Gemini\"; F32 (B7, What is GEO ¶1): \"You know how SEO helps people find you on Google? GEO does the same thing, but for AI.\"; F41 (W2, lead ¶1 s1): \"Generative engine optimization (GEO), also known as answer engine optimization (AEO)[1] and artificial intelligence optimization (AIO),[2] is the practice of improving visibility in responses generated by generative artificial intelligence (AI) systems.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside O1055-01, O661-01, O660-01", "archive_claims": [ "O1055-01", "O661-01", "O660-01" ] }, { "lineage": "its purpose and its stated limits", "field_claims": [ "F4", "F5" ], "received": "F4 (B11, line 11): \"This is a niche area, which is increasingly receiving attention from the community.\"; F5 (B11, line 11): \"This awesome‑listing is an attempt to bring together works in this space. This list is not complete and looking for your PRs to improve it.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-03", "archive_claims": [ "MMRS-03" ] }, { "lineage": "the contents: entries by year and open-source resources", "field_claims": [ "F6", "F7", "F9", "F10" ], "received": "F6 (B11, section headings): \"## 2026 … ## 2025 … ## 2024 … ## Open-Source Resources\"; F7 (B11, ## 2026, entries 1–2): \"IF-GEO: Conflict-Aware Instruction Fusion for Multi-Query Generative Engine Optimization … Multimodal Generative Engine Optimization: Rank Manipulation for Vision–Language Model Rankers\"; F9 (B11, ## 2025 entries 2, 4, 8; ## 2024 entry 5): \"Dynamics Of Adversarial Attacks On Large Language Model‑Based Search Engines … PoisonArena: Uncovering Competing Poisoning Attacks in Retrieval‑Augmented Generation … StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization … Adversarial Search Engine Optimization for Large Language Models\"; F10 (B11, ## 2025, entry 1): \"C-SEO Bench: Does Conversational SEO Work?, NeurIPS D&B 2025, [[Paper]](https://arxiv.org/abs/2506.11097) [[Code]](https://github.com/parameterlab/c-seo-bench) [[Dataset]](https://huggingface.co/datasets/parameterlab/c-seo-bench)\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-02, MMRS-09, MMRS-10, CAP-1-05, O833-01", "archive_claims": [ "MMRS-02", "MMRS-09", "MMRS-10", "CAP-1-05", "O833-01" ] }, { "lineage": "origin of the term: the 2023 paper", "field_claims": [ "F8", "F25", "F42", "F47" ], "received": "F8 (B11, ## 2024, entry 2): \"GEO: Generative Engine Optimization [[Paper]](https://arxiv.org/pdf/2311.09735)\"; F25 (B4, Research Papers, item 1): \"(2023) — The foundational research paper from IIT Delhi, Princeton, and Georgia Tech that introduced the term \"Generative Engine Optimization\" and tested optimization strategies.\"; F42 (W2, Terminology ¶1 s1): \"The term \"generative engine optimization\" was introduced in a 2023 paper by Pranjal Aggarwal and co-authors, later presented at the KDD 2024 conference.\"; F47 (W2, lead ¶2): \"This concept first appeared in response to generative AI technologies being integrated into mainstream search and information retrieval systems.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside O661-01, O64-01, O833-01", "archive_claims": [ "O661-01", "O64-01", "O833-01" ] }, { "lineage": "vendor entries in the list", "field_claims": [ "F11", "F12" ], "received": "F11 (B11, ## Open-Source Resources, entries 1 and 4): \"— Built by [Corank](https://corank.ai/). … — Built by [Assay](https://ai-fact-check-psi.vercel.app/).\"; F12 (B11, ## 2026, entries 4–5): \"(Rankfor.AI, 2026) … Empirical study showing 320% citation rate improvement when consistent information appears across 5-10 independent high-authority sources\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-04", "archive_claims": [ "MMRS-04" ] }, { "lineage": "tools in the list: measuring the composition", "field_claims": [ "F13", "F14", "F46" ], "received": "F13 (B11, ## Open-Source Resources, entry 4): \"reports how often the engine agreed with itself, so a claim about what an AI \"says\" can be separated from run-to-run variance\"; F14 (B11, ## Open-Source Resources, entry 1): \"client-side validator for GEO/AEO observation records that checks evidence completeness, citation-field consistency, timestamps, and duplicate run keys\"; F46 (W2, Tools ¶2): \"While the efficacy of third-party tools is debated within the overall GEO and SEO industries,\"", "receiving_text": "—", "translation": "untranslated: composed as received beside O653-01", "archive_claims": [ "O653-01" ] }, { "lineage": "homonym: Geoawesome", "field_claims": [ "F15", "F16", "F35", "F36", "F37", "F38" ], "received": "F15 (B2, page title): \"Geoawesome - Blog & Geospatial Community Platform\"; F16 (B2, home page, article list): \"The Living Library: Where Historical and Current Satellite Imagery Comes Alive … Sponsored Article … 07.22.2026\"; F35 (B8, oEmbed title (the card: YouTube · Geoawesome, 1:50, no title)): \"Reintroducing Ourselves as Geoawesome\"; F36 (B9, card snippet): \"Geoawesome. @geoawesome.digital. 21.1K subscribers•387 videos.\"; F37 (B9, channel description (og:description) ¶1): \"The world’s largest geospatial community is united by its belief in the power of location technology to transform the world for the better.\"; F38 (B9, channel description (og:description) ¶2): \"Since its humble beginnings on April 20th, 2011, Geoawesome, previously Geoawesomeness, has striven to be an open and inclusive platform for geospatial experts and enthusiasts\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-18", "archive_claims": [ "MMRS-18" ] }, { "lineage": "neighbour lists of GEO resources", "field_claims": [ "F17", "F21", "F22", "F23", "F26", "F29", "F30", "F31", "F33", "F34" ], "received": "F17 (B3, opening (blockquote)): \"A curated list of resources for optimizing content visibility in AI-powered search engines (ChatGPT, Perplexity, Google AI Overviews, Claude, etc.)\"; F21 (B3, Footnotes, key terms): \"**Entity Optimization** - Strengthening brand presence as a recognized entity across the web. … **E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)** - Quality signals that influence AI recommendations.\"; F22 (B3, opening, licence badge): \"License: CC0-1.0\"; F23 (B4, opening (blockquote)): \"A curated list of resources, tools, research, and guides for **Generative Engine Optimization (GEO)**\"; F26 (B4, License): \"This list is released under CC0.\"; F29 (B6, hero): \"SEO for the AI era. Free platforms and tools to get your brand discovered by ChatGPT, Perplexity, Gemini, and other AI engines.\"; F30 (B6, tool cards): \"Full Visibility Audit … Schema Generator … llms.txt Builder\"; F31 (B6, footer): \"Built by Dmitry Kargaev\"; F33 (B7, So what is this project? ¶1): \"Awesome GEO is a free, open-source collection of platforms where you can build your AI presence.\"; F34 (B7, How we score things ¶1): \"Each platform gets evaluated on domain authority, whether links are dofollow, how AI crawlers treat the site, and an overall GEO score.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-15, MMRS-16, MMRS-17, MMRS-25, CAP-1-06", "archive_claims": [ "MMRS-15", "MMRS-16", "MMRS-17", "MMRS-25", "CAP-1-06" ] }, { "lineage": "names of the practice", "field_claims": [ "F18", "F43", "F44" ], "received": "F18 (B3, opening, Also known as): \"**Also known as**: AI Search Optimization (AISO), Answer Engine Optimization (AEO), Large Language Model Optimization (LLMO), Generative AI Optimization, AI SEO, LLM SEO\"; F43 (W2, Terminology ¶1 s2): \"Several overlapping terms describe related practices, and usage varies across practitioners, vendors, and publications, with no consensus definition.\"; F44 (W2, Terminology ¶2 s1): \"optimizing for generative AI search is optimizing for the search experience, and thus still SEO.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside O791-01, O791-02", "archive_claims": [ "O791-01", "O791-02" ] }, { "lineage": "homonym: the Awesome GEE Community Catalog", "field_claims": [ "F27", "F28", "F39", "F40" ], "received": "F27 (B5, hero): \"A community data commons … 585 TB of open geospatial data, analysis ready inside Google Earth Engine.\"; F28 (B5, hero): \"Grassroots & unfunded since 2020\"; F39 (B10, page body ¶1): \"The Awesome GEE Community Catalog is an unfunded open source grassroots project with a mission to help collect community sourced and community generated geospatial datasets.\"; F40 (B10, page body ¶2): \"This catalog lives and serves alongside the Google Earth Engine data catalog.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-19", "archive_claims": [ "MMRS-19" ] }, { "lineage": "the collision: GEO and geo", "field_claims": [ "F45" ], "received": "F45 (W2, Terminology ¶3 s2): \"Profound describes AEO and GEO as the same practice but argues that \"GEO\" can be confused with geography.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside MMRS-05, MMRS-06, O661-04, CAP-1-03", "archive_claims": [ "MMRS-05", "MMRS-06", "O661-04", "CAP-1-03" ] } ], "receiving_texts": "equal-terms case: every field claim composed as received, beside the archive claims it stands with" }, "measure": { "rule": "v0.9 §4.10: KO_B sentences surviving in the KO at similarity ≥ 0.95, with positions (computed as apply_v09.py does: difflib.SequenceMatcher ratio, the best KO sentence for each KO_B sentence)", "v0.9": { "surviving": 0, "of": 9, "positions": [ null, null, null, null, null, null, null, null, null ] }, "opening_run": { "rule": "v0.9 §5.10 (equal-terms case): the field-only KO's sentences as the KO's opening run in their own order", "breach": false }, "blocks": { "rule": "v0.9 §4.1 (equal-terms and mixed cases): the KO does not open with the field as a block or close with the archive as one; sentences typed by the ledgers of the claims they cite (F field-only, A archive-only, M both)", "sequence": "MMFMFMFMMMAAMAAMAAAAMFAMAMA", "field_only_head": 0, "archive_only_tail": 1, "breach": false }, "max_similarity": [ 0.106, 0.099, 0.166, 0.143, 0.173, 0.165, 0.094, 0.369, 0.285 ], "ko_sentence_1_max_similarity_to_KO_B": 0.082 }, "homonyms": { "names": [ "Geoawesome (geoawesome.com; YouTube @geoawesome.digital), geospatial media and community", "Awesome GEE Community Catalog (gee-community-catalog.org; Earth Engine Data Catalog, community/sat-io), geospatial datasets", "'GEO' as the archive's own series code for the Geocoded Basin (EA-GEO-01, #689; its addendum #77): a homonym of the string inside the archive, on no card" ], "basis": "the MMRS record's disambiguation (Geoawesome: 'geospatial media, GIS, Earth observation'; the catalog: 'Google Earth Engine, community geospatial datasets') and negative tag ('NOT a geospatial ('geo') awesome list'); the Capture Registry's finding (CAP-1-06); the cards B2, B5, B8, B9, B10; the encyclopedia's report that 'GEO' can be confused with geography (F45). The other GEO lists (amplifying-ai/awesome-generative-engine-optimization, henu-wang/awesome-geo, aGEO at geo.deeflect.com) share the name or the class and are distinct entities, kept as relations and census candidates, never senses of the name. The archive-side homonym was found in the string pass and set aside (reading.json).", "distinct_entities": [ "amplifying-ai/awesome-generative-engine-optimization", "henu-wang/awesome-geo", "aGEO (geo.deeflect.com)", "presenc-geo-papers" ], "related_entities": [ { "slug": "presenc-geo-papers", "name": "Presenc AI — GEO academic papers 2026", "relation": "neighbour (MMRS relations.rel)" }, { "slug": null, "name": "amplifying-ai/awesome-generative-engine-optimization", "relation": "census candidate; disambiguated" }, { "slug": null, "name": "henu-wang/awesome-geo", "relation": "census candidate as 'henu-wang/awesome (Awesome GEO)'; disambiguated" }, { "slug": null, "name": "aGEO — Awesome GEO platforms (geo.deeflect.com)", "relation": "census candidate; disambiguated" } ], "substitutes": { "T1": [] }, "register": { "address_1": { "slug": "awesome-geo-aio-20261029", "obs_id": "OBS-3d26cbe75ddc" } } }, "notes": [ "One address, Google AI Overview (expanded), signed out, incognito, 2026-10-29: awesome-geo-aio-20261029 (OBS-3d26cbe75ddc, ADDR-913579b3c946, AXN:0AA9.CAPTURE.✖️🟢🫵🍃🎆♃), ten cards.", "Wikipedia: no article, redirect or search result for 'Awesome-GEO' (404s and an empty full-text search, saved). The class's article 'Generative engine optimization' exists and is ledgered (W2, F41–F47) on the brief's instruction; it names neither the list nor any awesome list and was not surfaced by T.", "Fetching: every reachable page saved verbatim with curl on 2026-10-29 between 05:07 and 05:10 UTC, raw and text with sha256 in field.json. github.com answered HTTP 403 to this session for all three repository pages (B1, B3, B4; the proxy's 403 bodies saved): B1's card title and snippet stand as its text and its README is the own page B11; B3's and B4's READMEs were fetched raw as those cards' texts (henu-wang's repository is awesome-geo, the card title being truncated to 'henu-wang/awesome'). The video card (B8) has no title or snippet; it was identified on the channel page by its duration (1:50) and admitted by its oEmbed title. The channel page (B9) is a script shell; its description was extracted from its og:description into B9.txt.", "The archive's deposits do not name the list or its maintainer (D 0, R 0 over 1,711 texts). At O-class the class term matched 216 sentences with an archive category in 56 deposits; 14 deposits admitted by reading and one (#653) through the hop (230 candidates, 215 deposits); the rest read and set aside as restatements of admitted lineages (S4), claims on other objects, citations, or the archive's own 'GEO' series code (reading.json).", "Defects found, reported and not fixed. (1) MMRS article, 'Place in the field' s1: 'kept without vendor notes' against the README, which credits two open-source entries to the companies that built them ('Built by [Corank]', 'Built by [Assay]'), lists a paper under its vendor's name ('Rankfor.AI, 2026') and carries a resource entry's '320% citation rate improvement' (F11, F12); carried as contested. (2) MMRS disambiguation label and census candidate 'henu-wang/awesome (Awesome GEO)' (url null) take the card's truncated title; the repository is henu-wang/awesome-geo (B4). The capture finding CAP-1-06 carries the same truncation. (3) Capture finding CAP-1-03 quotes the record's negative tag as 'NOT a geospatial awesome list'; the census reads \"NOT a geospatial ('geo') awesome list\" (not material). (4) #833 (The Summarizer as Horizon of Reception, related work and references) cites the GEO paper as 'Sharma, A. et al. (2024). Generative Engine Optimization. arxiv.'; the field (W2, B4) and the archive's own #661 give Pranjal Aggarwal and co-authors (arXiv 2311.09735, 2023; KDD 2024). (5) MMRS's '123 stars' and 'Fourteen pull requests' are not checked: github.com did not serve the repository page to this session. (6) The census candidates for amplifying-ai and henu-wang carry url null; their repositories are github.com/amplifying-ai/awesome-generative-engine-optimization and github.com/henu-wang/awesome-geo.", "Within the archive, carried as P_coh: #61 (April 2026) 'SPXI ⊇ GEO' (SPXI contains GEO's methods) against #1055 (July 2026) 'They cannot coexist within the same compositional practice' (open block).", "Field discrepancies, carried: the GEE catalog's size reads 587 TB on the card and 585 TB on the page fetched; the card for the video gives no title, and the identification is the extractor's.", "The case and ρ (decided): equal, ρ = extends; the MMRS record describes the list from its own repository and adds senses and limits on the field's object; the deposits' account of GEO extends the field's ontology of the class; the field holds the ontology, so the suppressed witness does not apply.", "Opening-run check (§5.10): KO sentence 1 is new (max similarity to any KO_B sentence 0.082); no KO_B sentence survives at ≥ 0.95 (highest 0.369); sentence types MMFMFMFMMMAAMAAMAAAAMFAMAMA (no field-only head, archive-only tail 1). The archive's account of the class (¶2) is a run of mostly archive-only sentences in the middle of the KO, interleaved with field claims where the field bears (sentences 13 and 16): the field has no claims on most of the senses the archive adds.", "An observation for the operator, not composed: the list's Open-Source Resources include two instruments that measure the composition layer itself (an observation-record validator and a run-to-run variance check, F13, F14), the kind of measurement the archive says GEO does not make (#653: 'GEO measures citation frequency'); the row composes both beside each other without a claim joining them." ], "composition_v09": { "source": "this row (composed directly; no rebuild/negative-of-the-negative/v09/awesome-geo-davidhuji.json)", "composer": "Claude (Opus 5.5), subagent, 2026-10-29", "defining_material_read": [ { "what": "MMRS record, census row", "file": "/home/claude/fleet/machinemediation-org/data/meta-aggregator/census.json (rows[slug == 'awesome-geo-davidhuji'], schema_note, candidates)", "read": "whole" }, { "what": "MMRS record, article", "file": "/home/claude/fleet/machinemediation-org/scripts/meta_aggregator/articles.py (ARTICLES['awesome-geo-davidhuji'])", "read": "whole" }, { "what": "MMRS record, rendered", "file": "/home/claude/fleet/machinemediation-org/aggregators/awesome-geo-davidhuji/index.html", "read": "text, for agreement with the sources" }, { "what": "capture record", "file": "data/EA-WG-CAPTURES-01.json (awesome-geo-aio-20261029)", "read": "transcript, transcript_raw, cite_list, d, reading, findings, analysis" }, { "dep": 833, "file": "data/texts/AXN-034E-text.md", "read": "related work and references, around the admitted paragraph" }, { "dep": 1055, "file": "data/texts/AXN-042B-text.md", "read": "kernel, disambiguation ground and what the packet does not claim" }, { "dep": 661, "file": "data/texts/AXN-020C-text.md", "read": "§1–§2.1, the problem, what GEO does and does not do" }, { "what": "the specification", "file": "data/texts/AXN-0700-text.md", "read": "§0–§6" } ], "cuts": [], "notes": "equal case; KO 27 sentences, all 47 field and 62 archive claims cited; P body 238 words; KO_B 9 sentences, none surviving at ≥ 0.95" }, "field_by_origin": { "note": "The field B by origin (v0.9 §3.1(a); the brief's three origins): cards B1–B10 (the rail), the own page B11 (the README of card B1's repository), Wikipedia W1 (no article for the entity) and W2 (the class's article). Grouped here; the flat list is row.field.", "cards": [ "B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B9", "B10" ], "own_pages": [ "B11" ], "wikipedia": [ "W1", "W2" ], "unreachable": [ "B1" ], "title_only": [ "B8" ], "wikipedia_state": "no article for the entity: 'Awesome-GEO' and 'Awesome_GEO' answer 404 as raw wikitext, the rendered page answers 404 ('Wikipedia does not have an article with this exact name.'), a full-text search for the quoted name returns no results, and no redirect exists. The class has an article, 'Generative engine optimization' (W2, revision of 2026-10-29), which names neither the list, DavidHuji, nor any awesome list, defines GEO (also AEO, AIO) as 'the practice of improving visibility in responses generated by generative artificial intelligence (AI) systems', dates the term to a 2023 paper by Pranjal Aggarwal and co-authors (KDD 2024), finds 'no consensus definition', and reports Profound's argument that 'GEO' can be confused with geography (F41–F47)", "wikipedia_record": { "id": "W1", "origin": "wikipedia", "result": "no article for the entity; an article for the class", "checked": "2026-10-29 05:09–05:10 UTC", "requests": [ { "url": "https://en.wikipedia.org/w/index.php?title=Awesome-GEO&action=raw", "http": 404, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W_Awesome-GEO.wiki", "sha256": "74679f1bff8a03d649b7bc78dc190d8b09b67166f84cdf86579e94a5e6cfcb34" }, { "url": "https://en.wikipedia.org/w/index.php?title=Awesome_GEO&action=raw", "http": 404, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W_Awesome_GEO.wiki", "sha256": "3ac2dbd15255ebb4115c155e12fa7bdf8ad8c23b873819c05912556078c6dfc4" }, { "url": "https://en.wikipedia.org/wiki/Awesome-GEO", "http": 404, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W1.html", "sha256": "d9b5aa97e1be9717a01eb04d1a243ba2dcf90cb166baf28637d6c386447b58fc", "says": "Wikipedia does not have an article with this exact name." }, { "url": "https://en.wikipedia.org/w/index.php?search=%22Awesome-GEO%22&title=Special%3ASearch&profile=advanced&fulltext=1&ns0=1", "http": 200, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W1-search.html", "sha256": "ca13555ec6c6a8c33b047d21de1b89395e9ddf1798390d5a9060697349041059", "says": "There were no results matching the query." }, { "url": "https://en.wikipedia.org/w/index.php?title=Generative_engine_optimization&action=raw", "http": 200, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.wiki", "sha256": "9da191442c0b49b86dbf74029e35c0ba84dadd84452a31818fd609333e1e5318" }, { "url": "https://en.wikipedia.org/w/index.php?title=Generative_Engine_Optimization&action=raw", "http": 404, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W_Generative_Engine_Optimization.wiki", "sha256": "dcc2e46aca2f4a3a4685c9d54caa4a0b48dedcffd058226a6bbe1946e0ffadf1", "note": "the capitalised title is not a redirect" }, { "url": "https://en.wikipedia.org/wiki/Generative_engine_optimization", "http": 200, "file": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.html", "sha256": "f7b9818401103484bcbff0b85f0586abe6ee6514f816c939883ae09431a809fc" } ], "redirect": "none (Awesome-GEO and Awesome_GEO answer 404; no redirect page)", "note": "English Wikipedia has no article, redirect or mention for the entity on 2026-10-29: the raw-wikitext requests for 'Awesome-GEO' and 'Awesome_GEO' answer 404, the rendered page answers 404 with 'Wikipedia does not have an article with this exact name.', and a full-text search for the quoted name returns no results. The class has an article: 'Generative engine optimization' (W2, raw wikitext and rendered page saved), which names neither the list nor any awesome list, DavidHuji, or any of the card rail's sources; it is ledgered (F41–F47) as the class's encyclopedia account, on the brief's instruction to check it. 'Generative Engine Optimization' (capitalised) is not a redirect (404). W2 was not surfaced by T." }, "sources": [ { "id": "B1", "origin": "card", "role": "Overview card 1; also the own page the MMRS record cites (github.com/DavidHuji/Awesome-GEO, basis operator)", "card": "GitHub — GitHub - DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization) · GitHub", "url": "https://github.com/DavidHuji/Awesome-GEO", "kind": "code repository page (GitHub · DavidHuji/Awesome-GEO): the entity", "surfaced_by_T": [ { "slug": "awesome-geo-aio-20261029", "card": 1 } ], "files": { "B1-github-page-403.html": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/B1-github-page-403.html", "sha256": "b3e03aaaff81d68730d67392a135ac3fdfdf022880c66632ab188d2fe084cda3" }, "B1.txt": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/B1.txt", "sha256": "b3e03aaaff81d68730d67392a135ac3fdfdf022880c66632ab188d2fe084cda3" } }, "fetched": { "at": "2026-10-29T05:07:34Z", "http": 403, "url": "https://github.com/DavidHuji/Awesome-GEO", "raw": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/B1-github-page-403.html", "raw_sha256": "b3e03aaaff81d68730d67392a135ac3fdfdf022880c66632ab188d2fe084cda3", "text": [ "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/B1.txt" ] }, "card_title": "GitHub - DavidHuji/Awesome-GEO: Awesome list for research on GEO (Generative Engine Optimization) · GitHub", "card_snippet": "Awesome‑Generative‑Engine‑Optimization Generative Engine Optimization (GEO), is a paradigm to aid content creators in improving their content visibility in gene...", "card_note": null, "unreachable": true, "names_operator": "yes ('DavidHuji' in the card title; the 403 body names no one)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, MMRS, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "note": "github.com answered HTTP 403 to this session (the session proxy's message that GitHub access to the repository is not enabled), saved as B1-github-page-403.html and copied as B1.txt; the repository's README was fetched verbatim from raw.githubusercontent.com as B11 (own page). B1 and B11 are one source: B1 the surfaced instance, its card title and snippet its own text here; B11 its fetched text. The card's snippet is the README's line 9. 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The .html and .txt are the same Markdown. Entries counted by the extractor: 2026, 5; 2025, 9; 2024, 8; Open-Source Resources, 5; 27 in all, the MMRS record's 'about 27'. The README carries no licence statement and no date; its banner image is named 'Screen Shot 2024-11-18'" }, { "id": "W2", "origin": "wikipedia", "url": "https://en.wikipedia.org/wiki/Generative_engine_optimization", "kind": "Wikipedia article for the class (Generative engine optimization); the entity has none", "files": { "W2.wiki": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.wiki", "sha256": "9da191442c0b49b86dbf74029e35c0ba84dadd84452a31818fd609333e1e5318" }, "W2.html": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.html", "sha256": "f7b9818401103484bcbff0b85f0586abe6ee6514f816c939883ae09431a809fc" }, "W2.txt": { "path": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.txt", "sha256": "dbeb08a0c511de4e06e168fbba0d325c55bfcf6cac5e36233563725fdcf6fd88" } }, "fetched": { "at": "2026-10-29T05:09:07Z (raw) / 05:09:24Z (rendered)", "http": 200, "url": "https://en.wikipedia.org/w/index.php?title=Generative_engine_optimization&action=raw", "raw": "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.wiki", "raw_sha256": "9da191442c0b49b86dbf74029e35c0ba84dadd84452a31818fd609333e1e5318", "text": [ "datasets/negative-of-the-negative/v2/intake/awesome-geo-davidhuji-20261029/W2.txt" ] }, "surfaced_by_T": false, "names_operator": "no", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, machinemediation, MMRS, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "admitted": "the class's article, checked on the brief's instruction ('Wikipedia: check \"Generative engine optimization\"; record what exists'); the entity has no article (W1). 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