AXN:09EC.CAPTURE — scientific training-layer literature

AXN:09EC.CAPTURE is the position of the Capture Registry address for the query “scientific training-layer literature”. Each observation at the address (one surface, one date) is one AXN, its glyphs derived from the SHA-256 of the observation sealed with its analysis and measures.

`AXN:09EC.CAPTURE.➕🗼△🎪🔺♊`

Observation: Google AI Overview, 2026-10-17 · the capture
Description: SCIENTIFIC TRAINING-LAYER LITERATURE: the AI Overview gives #176's paradigm 'proposed by researchers like Lee Sharks' — a human exposition layer and an author-verified training layer per paper, the TLL-P / R / G protocol suite and six machine-reception layers from training to agentic use — naming the Alexanarch protocols as the exact match and keeping SciLitLLM and 'learning in layers' apart.
Reading: The innocent reading first: 'a highly specific, emerging architectural paradigm in scientific communication proposed by researchers like Lee Sharks' — papers published with a human exposition layer and 'an explicit, author-verified "training layer"'; the TLL protocol suite (TLL-P / R / G); six machine-reception layers (training, indexing, embedding, retrieval, composition, agentic use). #176 throughout: 'a dual-layer scientific publication architecture, and the TLL-P / TLL-R / TLL-G protocol suite', the six layers, the genre distinguished from 'machine-reception literature'. The Overview names the exact match ('the Alexanarch Protocols for Scientific Training-Layer Literature') and sets two namesakes beside it: SciLitLLM's literature fine-tuning and 'learning in layers' in study technique.
Analysis: At the term, the Overview composes #176 at its grain — the dual-layer paper, TLL-P/R/G, six reception layers — attributed to 'researchers like Lee Sharks', and keeps two namesakes apart. Seated 2026-10-17 from the operator's paste.
Match: BROAD MATCH — SCIENTIFIC TRAINING-LAYER LITERATURE — #176 AT ITS GRAIN: THE DUAL LAYER, TLL-P/R/G, SIX RECEPTION LAYERS
PER: 0.25 — Retained: the author, the institution and visible sources. Lost: identifiers.
Citations: 10 (0 archive-controlled)
Sealed observation: /data/captures/sealed/scientific-training-layer-literature-aio-20261017.json — SHA-256 902a9885d0abd35225679fec00c72dc1d49967c5162e7202c39d47a0c72b1f33