Dispositif d'évaluation pour un certificat d'aptitudes cliniques : quelles mesures pour quelles compétences ?
Bibliographic record
Abstract
Cette communication présente les premiers résultats de l'étude de la mise en place d'un certificat d'aptitude clinique à travers la conception et la mise en oeuvre d'un environnement informatique. Cet environnement informatique vise d'une part à équiper cet examen, et d'autre part à mener une démarche réflexive le concernant. Les résultats des étudiants à cet examen montrent une non redondance avec ceux des épreuves classantes typiques de ce parcours de formation. En confrontant les retours des étudiants au travers de questionnaires anonymes et l'étude du dispositif de formation lui-même, nous interrogeons l'approche qui le sous-tend concernant les compétences en général, et les compétences relationnelles en particulier.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".