MétaCan
Menu
Back to cohort

On the Structural Dependencies of Intelligence: Coherence, Preservation, and the Role of Emergence (v1.2)

2025· preprint· W7148310596 on OpenAlexaboutno aff
Robin Bruce Thacker

Bibliographic record

VenueFigshare · 2025
Typepreprint
Language
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsnot available
Fundersnot available
KeywordsFalsifiabilityDependency (UML)CounterexampleCoherence (philosophical gambling strategy)Subject (documents)TRACE (psycholinguistics)Zero (linguistics)Dependency theory (database theory)

Abstract

fetched live from OpenAlex

We report a structural dependency governing stable reasoning in language models: λ[C ≥ P ≥ E], where Coherence bounds Preservation, which bounds Emergence. Across 420 blind evaluations of 140 reasoning traces from 28 architectures, zero counterexamples were observed. Three non-circularity tests confirm the pattern is intrinsic to the data. The dependency is falsifiable by a single stable trace where E > P. None were found.Version 1.2. Originally published on Zenodo (DOI: 10.5281/zenodo.17858943) on December 8, 2025. No content changes from v1.1. See Version History in manuscript for full provenance.Note: The methods and frameworks described in this paper are the subject of Canadian Patent Application CA 3294110. This work is available for non-commercial research, academic study, and educational use without restriction. Commercial use may require a separate license. Contact the author for details.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.090
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.006
Scholarly communication0.0040.008
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.298
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueFigshareSame topicLanguage and cultural evolutionFrench-language works237,207