{
 "row": "aeovision-geo-papers",
 "address": "aeo vision top arxiv papers geo",
 "entity": "AEO Vision's article \"Top 12 Arxiv Papers for Generative Engine Optimization in 2026\" (aeovision.ai/articles/top-arxiv-papers-for-generative-engine-optimization/, dated 15 July 2026, byline AEO Vision Content Team): a vendor list of 12 arXiv papers, each with authors, arXiv identifier, summary and a 'takeaway for teams', a quick-reference table, closing on AEO Vision's measurement product; formalized in the MMRS meta-aggregator record of 2026-10-28 (corrected 2026-10-29), census row aeovision-geo-papers",
 "procedure": "EA-NEGONT-02 v0.7 §3.4 (D/R/O), working; not frozen",
 "config": {
  "row": "aeovision-geo-papers",
  "address": "aeo vision top arxiv papers geo",
  "addresses": [
   "aeo vision top arxiv papers geo"
  ],
  "entity": "AEO Vision's article \"Top 12 Arxiv Papers for Generative Engine Optimization in 2026\" (aeovision.ai/articles/top-arxiv-papers-for-generative-engine-optimization/, dated 15 July 2026, byline AEO Vision Content Team): a vendor list of 12 arXiv papers, each with authors, arXiv identifier, summary and a 'takeaway for teams', a quick-reference table, closing on AEO Vision's measurement product; formalized in the MMRS meta-aggregator record of 2026-10-28 (corrected 2026-10-29), census row aeovision-geo-papers",
  "row_type": "C (public entity on which the archive bears: a curated list, a vendor article; an entity of the MMRS meta-aggregator)",
  "aliases": [
   {
    "pattern": "\\bAEO\\s?Vision\\b",
    "flags": "i"
   },
   {
    "pattern": "\\baeovision(\\.ai)?\\b",
    "flags": "i"
   },
   {
    "pattern": "\\bTop 12 ar[Xx]iv Papers\\b",
    "flags": "i"
   }
  ],
  "classes": [
   {
    "term": "generative engine optimization (GEO) research lists",
    "pattern": "\\b(generative engine optimi[sz]ation|GEO)\\b",
    "flags": "",
    "basis": "field: B8 (the entity's own page), title 'Top 12 Arxiv Papers for Generative Engine Optimization in 2026' and FAQ 'Why include RAG papers in a GEO list?'; ¶2 'This roundup highlights the top 12 arXiv papers for Generative Engine Optimization'; beside it in the field, lists of the same class: B4 (GeoReady, 'GEO Research — Papers Behind AI Search Visibility'), B5 (AEO VC, 'Academic research and studies on AEO, GEO, and AI-powered search optimization'), B2 (LinkedIn, 'Top 6 Research Papers & Studies on GEO & AEO', card title)"
   }
  ],
  "classes_note": "One class, sourced from the field by locus: the entity places itself as a list of research on generative engine optimization (B8, title, ¶2 and FAQ 'a GEO list'), among other GEO research lists on the rail (B4, B5, B2). The pattern is 'generative engine optimization' or the acronym GEO, case-sensitive, so that 'geo' as geography or a domain fragment is not matched. O-class admits only a sentence that applies an archive category (a concept it defines, an operator, a mint) to GEO as a class, its research or its lists; a sentence that names GEO in passing, lists it among terms, or uses it as a bare search term is not admitted. The MMRS record's class for the entity (the optimization basin, 'the research gathered as the warrant for a measurement product') is an archive source, ledgered as MMRS claims and not run as an O-class here, since the brief confines classes to what B sources. No field source names the archive. The aliases are the vendor's name (with and without the space), its domain and the article's title phrase. Admission by reading (§3.4): a candidate is admitted when its sentence or paragraph makes a claim bearing on AEO Vision or its list (D), states a relation between it and an archive object (R), or applies an archive category to it or to GEO as a class (O).",
  "exclude_deposits": [],
  "notes": "entity-keyed pass, 2026-10-29, on the brief rebuild/negative-of-the-negative/v09/BRIEF-NEW-ROW-AGGREGATOR.md; address 'aeo vision top arxiv papers geo' (aeo-vision-top-arxiv-papers-geo-aio-20261029, OBS-b1f1fee164cd, ADDR-147b2c822d63), Google AI Overview (expanded), signed out, incognito. The archive's own records of the entity (the Capture Registry's findings and analysis at the capture, the MMRS meta-aggregator record) are ledgered beside the deposits as CAP-1-NN and MMRS-NN. Second pass: one citation hop forward and back from the deposits admitted by reading at O-class (#61, #64, #72, #172, #510, #655, #659, #660, #661, #670, #791, #1055, #1638, #1643, #1686).",
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   64,
   72,
   172,
   510,
   655,
   659,
   660,
   661,
   670,
   791,
   1055,
   1638,
   1643,
   1686
  ]
 },
 "texts_scanned": 1711,
 "counts": {
  "D_sentences": 0,
  "D_deposits": 0,
  "R_sentences": 0,
  "R_deposits": 0,
  "O_direct": 0,
  "O_class": 215,
  "O_deposits": 55,
  "H_candidates": 216
 },
 "per_deposit": {
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  "R": {},
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   "89": 1,
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   "1686": 3
  }
 },
 "registry_entity_triples": [],
 "integrity_S5": [],
 "sha256": {
  "candidates-D.jsonl": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
  "candidates-R.jsonl": "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855",
  "candidates-O.jsonl": "f58bb5fc4a3f6ef5b61d30cb6403eeab7a49b6c79d0c8545c99eaefd59afe3ff",
  "candidates-H.jsonl": "8ca6191bac4e626be7e8ac654ada68f5b968953d59b0c7343342b6a769b74617"
 },
 "category_vocabulary": {
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 },
 "note": "Candidates by string only. Admission by reading, recorded in the row's reading file; nothing here is admitted."
}