Mise en ligne d’outils pédagogiques : une panacée pour l’enseignement de la traduction médicale ?
Bibliographic record
Abstract
Les contraintes de l’enseignement de la langue et de la traduction médicales résultent non seulement de la complexité de la matière, mais aussi de la conjugaison de deux facteurs antagonistes : d’une part, les acquis préalables des étudiants sont hétérogènes ; d’autre part, les exigences du marché du travail sont élevées. Le présent article fait état de la mise en oeuvre de sites utilisant la plateforme WebCT, qui permet la mise en ligne de différents outils pédagogiques. L’objectif est de compléter les cours donnés en classe et d’ajouter à l’approche pédagogique traditionnelle des outils qui favorisent la progression individuelle de l’étudiant et lui offrent une mise en situation dans des conditions évoquant la vie professionnelle.
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 | 0.025 | 0.050 |
| 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 | 0.017 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".