Le recours aux modèles dans la philosophie expérimentale selon le Neues Organon de Lambert
Bibliographic record
Abstract
Cette étude entend établir comment Lambert, dans le Neues Organon, conçoit la mise en forme des apparences sensibles de façon à constituer un savoir mixte conforme au système des vérités rationnelles. Ce savoir, étayé suivant des degrés assignables de probabilité, est susceptible de fonder et de baliser la méthodologie des sciences de la nature. Il s’agit notamment de déterminer comment les apparences sensibles peuvent se prêter à la construction d’hypothèses valides. Dans cette démarche, Lambert accorde un rôle particulier aux modèles dont le savant se sert pour figurer l’ordre de génération des phénomènes et leur rapport à la structure objective du monde. Il s’agit ici d’éclairer la façon dont Lambert se représente l’explication en philosophie expérimentale, les modalités de transposition des concepts empiriques en concepts théoriques, et le caractère provisoire et révisable des inférences théoriques.
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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 | 0.018 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".