Aziel Library

12 views · 22 downloads

/aziellibrary/cnlt1-canonical-normalized-lexical-transcription-readme

CNLT-1: Canonical Normalized Lexical Transcription v1
22 Aug 2026

PURPOSE
CNLT-1 is a structural proto-transcription, not plaintext. It rewrites each RF1b/CFST-1 token as:
L=<left physical operator> | LEMMA=<anonymous invariant body ID>[<body>] | R=<right physical operator> | STATE=<5-state grammar class>.

EVIDENCE FOR THE LEMMA LAYER
1. Internal family-body sequences agree between directly aligned ZL and GC tokens slightly more often than complete family sequences.
2. Across ZL, GC and RF, different edge-marked surface forms sharing the same internal body have significantly more similar non-adjacent within-line body contexts than frequency- and ending-state-matched forms with different bodies.
3. This direction holds in 15/15 page-group folds.
4. This supports treating the body as a lemma-like invariant for structural analysis. It does NOT establish pronunciation, language, or meaning.

CONTEXT INVARIANCE TEST
- Tokens: simple STA family sequences of length >=3.
- Body: token sequence after removing one physical family at each edge.
- Surface variants: distinct complete family sequences sharing a body.
- Context: bodies at token distance 2..5 within the same physical line; immediately adjacent tokens excluded to avoid simply re-measuring the known edge grammar.
- Metric: Jensen-Shannon divergence of context distributions.
- Control: different-body surface forms matched approximately on frequency and final-family/state class.
- Full corpus: one-sided paired Wilcoxon across eligible body families.
- Robustness: five page-group partitions in each ZL/GC/RF corpus.

INTERPRETATION
CNLT-1 is the closest supported normalized transcription currently available in this project. Anonymous lemma IDs are deliberately semantic-free.

Aziel Eliab
research, philosophy, Voynich
CNLT1 Canonical Normalized Lexical Transcription — README
ABAD, Voynich, CNLT1, Aziel

Download Counted download

Triad score

One combined report card from SPRE, CLCE.

TRIAD_V3: public combined = triad_cycle_mean = mean of all ordered pairings factor_i × factor_j among applicable factors of {physics, linguistics, bayesian, truth_formula, CLCE, SPRE} (36 when all six apply, including diagonals). Also stored: geometric_mean_applicable = (Π applicable engines SPRE/CLCE/PLR)^(1/n). Named axis products: physics×linguistics, bayesian×truth_formula, CLCE×SPRE. Bayesian is LIKELIHOOD of internal consistency, unranked, never a shelf sort key. triad_raw freezes to content SHA-256 at first REVIEW_SCORE. Downloads verify bytes and do not mint a new mean. No collection offset. Display is round(combined × 100) and is never written back into combined. How it's scored.

Status lights

Green means go. Yellow means read again. Red means stop and check. Easy enough for a 6th grader; kept for government use.

Structure — Green

Every file was hashed and checked.

SPRE — Green

Green: we can see where this file came from and what it is.

CLCE — Red

These stories do not fully match. The title, the notes, and the real file are talking about different stuff.

Poison — Green

Green: this does not look like a poison shell.

{ "schema": "aziel.lattice.anchor.v1", "kind": "aziel-corpus.recalibrate_v3", "carrier": "AzielTether", "author": "Aziel Eliab", "record_id": "AZDOC-D409A74F7D77", "run_id": null, "media_kind": null, "vibe_digest": null, "library": "aziel", "content_sha256": "3f4cac06494abb43f91bed1c0029532b5296d0b8b2c643bed1234086075279b1", "structure": { "ok": true, "file_count": 1 }, "spre": { "pc": 0.83, "band": "strong", "limitation": "SPRE scores provenance completeness. It does not assert criminal guilt. Advisory only. Author Aziel Eliab.", "applicable": true }, "clce": { "triple": 0.0426, "pairwise_avg": 0.2786, "advisory": true, "applicable": true }, "plr": { "applicable": false, "status": "not_applicable" }, "triad": { "combined": 0.4888, "display": 49, "ready": true, "formula": "TRIAD_V3: public combined = triad_cycle_mean = mean of all ordered pairings factor_i × factor_j among applicable factors of {physics, linguistics, bayesian, truth_formula, CLCE, SPRE} (36 when all six apply, including diagonals). Also stored: geometric_mean_applicable = (Π applicable engines SPRE/CLCE/PLR)^(1/n). Named axis products: physics×linguistics, bayesian×truth_formula, CLCE×SPRE. Bayesian is LIKELIHOOD of internal consistency, unranked, never a shelf sort key. triad_raw freezes to content SHA-256 at first REVIEW_SCORE. Downloads verify bytes and do not mint a new mean. No collection offset. Display is round(combined × 100) and is never written back into combined." }, "bayesian": { "posterior": 0.6667, "unranked": true, "note": "Unranked likelihood of internal consistency. Never used to sort the shelf. Not world accuracy." }, "possibility": { "possibility": null, "kind": "HEURISTIC", "refuse": "PENDING_ANCHORS", "unranked": true, "not_truth": true }, "quarantine": null, "zsolver": { "status": "not_applicable", "applicable": false, "seed_corpus": false, "baseline": false }, "ledger_entry_hash": "8c10aad2f5ca3c220a348f0d145549c1c92bec907396acb78ad7e5ba37502e4c", "verified_utc": "2026-10-04T04:16:28.407Z", "note": "Public HTTPS site is not a mesh. AzielTether carries this tip. Survival interdependence with GodLock and other Aziel software is via downloadable tether + Worker bootstrap APIs." }

CNLT1 Canonical Normalized Lexical Transcription — README

Triad score

Status lights

SPRE, CLCE

Derived artifacts

Temporal-geospatial events

Bayesian peer score

Possibility score

Peer-to-peer review