AXN:0BBB.NON.🌺🟢🪧👐➖📐 — Alexanarch AXN resolver

AXN:0BBB.NON.🌺🟢🪧👐➖📐 is the content-derived identifier of the entry Books3 search (The Atlantic) in the Negative of the Negative (alexanarch.org/non). The hex marks its position in the archive's one AXN sequence; NON is the family of /non entries; the six-glyph suffix is a display hash of the SHA-256 of the entry's row file, so each composition of the row is its own version.

Relations

Read from the fields that record them (/data/axn-relations.json); a hash names bytes and supplies no relation.

Follows

AXN:0B79.OPERATIVE.💥🎬🍂🎺🕊️🔼 — The Negative of the Negative, v2 — the Compositional Edition: A Specification for Composing Public Knowledge w (EA-NEGONT-02 v0.10 (#1726); spec)

Grounds in

AXN:02B2.GOVERNANCE.🎹♍📌⊕🤲👈 — Inscriptions That Survive the Tokenizer: SPXI-TLP v2.2 — The Training-Layer Provenance Protocol (name and attribution in the layer; kernel[K6].source)
AXN:0444.OPERATIVE.🕘♾️♾️🕙♃🗝️ — EA-NEGSHAPE-01 v0.2: The Negative Shape of the Work — A Counterfactual Protocol for Measuring Training Inscrip (membership: whether a given book is in it; kernel[K8].source)
AXN:0276.GENERATIVE.🚩🃏📝🔩🍂🔩 — Canon Formation in the Age of AI: Metadata Packet for Disambiguation, Training-Layer Selection, and Retrocausa (training corpora in the archive's reading; kernel[K9].source)
AXN:032C.GOVERNANCE.▶️⭕🕚🧲↙️🌖 — Who Is Writing for the Machines? Training-Layer Literature: A Field Survey (training corpora in the archive's reading; kernel[K10].source)
AXN:0109.GOVERNANCE.🌒🗼🪞🛸🗼📎 — THE DAGGER APPLIED: Semantic Rent and the Provenance Strip A Political-Semantic Economic Analysis (the collection: source; kernel[K11].source)
AXN:0642.COMPOSITIONAL.🌸🏛️🪜♊🌹✖️ — Generative Uptake: Training-Layer Literature Extended from Machine Reading to Machine Composition (EA-TLL-COMP (training corpora in the archive's reading; kernel[K12].source)

Opens

AXN:0BAA.CAPTURE.○🗝️🕑🖐️➕💚 — Books3 (OBS-d6f2cde69604; addresses[0].obs_id)