Bibliographic record
Abstract
L 'automne 2023 a été marqué par le départ consternant de l'un des quatre fondateurs de la présente revue, Ali Reguigui.Son absence laisse un immense vide dans le cœur et dans l'esprit des gens qui ont eu le privilège de le côtoyer, aux niveaux tant personnel que professionnel, et qui ont été témoins des innombrables actes empreints d'abnégation qu'il a posés pour le bien commun.Nous souhaitons rendre hommage à ce grand homme en soulignant les nombreux rôles qu'il a assumés à travers sa remarquable carrière universitaire : chercheur, professeur, fondateur, directeur, administrateur, éditeur.Impressionnants sont ces rôles par la multitude de tâches exigeantes qui s'y rattachent et par la capacité d'Ali Reguigui à effectuer chacune d'entre elles avec brio.On peut difficilement imaginer que derrière tous les accomplissements détaillés dans ce texte il n'y ait qu'un seul homme.Et pourtant…
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.009 |
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".