On the Structural Dependencies of Intelligence: Coherence, Preservation, and the Role of Emergence (v1.2)
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".