Bibliographic record
Abstract
Dans les textes médicaux et para-médicaux, anglais ou français, les formes passives ne représentent que 33 % ou 42 % de toutes les formes verbales relevées, selon que les participes passés utilisés seuls sont considérés respectivement comme des adjectifs ou comme des formes verbales. Ce pourcentage semble cependant être influencé par la nature du texte. En français médical ou para-médical, le nombre déformes verbales actives construites avec le sujet « on » [on + verbe actif] ou déformes verbales pronominales est faible. La nature du texte semble influer sur la fréquence du « on » mais non sur celle des verbes pronominaux. Toutefois, traduire un verbe passif d'un texte médical ou para-médical par [on + v. actif] ou par un verbe pronominal fait peut-être « français » mais ne fait ni « scientifique » ni « médical ».
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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; both teacher heads agree on what is shown here.
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".