Bibliographic record
Abstract
What is complexity?The present work will offer a description of complex systems based on two general principles: juxtaposition of similar units and then integration of these units, once modified, into structures at a higher level of which they become parts.As in a mosaic, however, these parts within the higher level or structure, retain some independent properties and autonomy.The model is based directly on observations of living organisms: cells or organs retain their autonomy functioning within a given organism, and individual organisms have autonomy when functioning as part of a population or society.Qu'est-ce que la complexité ?Le présent travail offre une description des systèmes complexes basés sur deux principes généraux : la juxtaposition d'unités similaires et l'intégration de ces unités, une fois modifiées, dans des structures de niveau supérieur dont ils deviennent parties.Comme dans une mosaïque, cependant, ces parties conservent certaines propriétés indépendantes et de l'autonomie.Le modèle est basé directement sur les observations des organismes vivants : des cellules ou des organes conservent leur autonomie de fonctionnement au sein d'un organisme donné, et les organismes individuels ont une autonomie lorsqu'ils fonctionnent dans le cadre d'une population ou d'une société.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.185 | 0.074 |
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".