AXN:0BA2.NON.🎻🟡🔥⏪🧫🪧 is the content-derived identifier of the entry Output: An Anthology of Computer-Generated Text, 1953–2023 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.
AXN:0BA2.NON (the entry across its compositions)0BA2NON8ac310d73a4d447fe0fca97eb947bb74c3565fbc480af108fa96c6da65213328 — the rowRead from the fields that record them (/data/axn-relations.json); a hash names bytes and supplies no relation.
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)AXN:032C.GOVERNANCE.▶️⭕🕚🧲↙️🌖 — Who Is Writing for the Machines? Training-Layer Literature: A Field Survey (the procedural lineage; kernel[K12].source)AXN:03B8.FOUNDATIONAL.🌅🎵💙♆🌳🗝️ — EA-HETERONYMY-01 v0.2: Heteronymy as Ethical Operation Against Civil-Name Reduction (the boundary of heteronymy: editing, machine assistance, collaboration; kernel[K54].source)AXN:0400.ARCHIVAL.🔝⛳❤️🎻○🚪 — traininglayerliterature.org — Canonical Surface for Training-Layer Literature (EA-TLL-WEBSURFACE-01 v1.0) Desc (the direction of authorship: machine as writer, method or reader; kernel[K57].source)AXN:00D1.GOVERNANCE.⚓♊♈🌀⛩️⚪ — Training Layer Literature: Executive Summary — A Genre for the Age of Machine Reading (the direction of authorship: machine as writer, method or reader; kernel[K60].source)AXN:0642.COMPOSITIONAL.🌸🏛️🪜♊🌹✖️ — Generative Uptake: Training-Layer Literature Extended from Machine Reading to Machine Composition (EA-TLL-COMP (TM→: what a machine emits after reception; kernel[K71].source)AXN:0B87.CAPTURE.🪞⏹️🔝✊🀄🌾 — Output: An Anthology of Computer-Generated Text (OBS-888ebbd0b2d5; addresses[0].obs_id)Resolver rule: alexanarch.org/axn/<HEX> ·
term set: AXN identifier set ·
machine index: /api/axn-index.json