Bibliographic record
Abstract
Jusqu’à Blaise Pascal, le hasard désigne ce qui se produit en dehors de tout dessein humain ou divin et de tout ordre stable. Après lui, on cherche à préciser de façon constructive ces trois types d’exclusion, ce qui amène à définir les événements merveilleux, les événements aléatoires et les événements accidentels. Chacune de ces trois démarches a ses avantages et ses inconvénients. La première rend compte de tout ce qui étonne, mais écarte la liberté et le miracle et ne permet ni vérification, ni prévision, ni décision. La seconde permet des prévisions et des vérifications expérimentales, mais son emploi ne peut se généraliser sans entrer en conflit avec le déterminisme, qui la considère comme une illusion. La troisième explique beaucoup de choses par la rencontre de séries causales indépendantes, mais ce faisant elle exclut toute finalité. Il faut faire très attention à ne pas les confondre.
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 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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".