« Choisir avec soin » et la gestion des antimicrobiens : un même souci de réduire les soins inutiles
Bibliographic record
Abstract
On constate dans le milieu médical un mouvement croissant qui reconnaît que certains examens, certains traitements ou certaines interventions médicales n'ajoutent aucune valeur pour les patients, et peuvent même être nocifs.La campagne « Choisir avec soin » est une campagne populaire dirigée par des médecins, qui vise à engager le dialogue entre les médecins et les patients sur l'utilisation excessive d'examens, de traitements et d'interventions médicales inutiles, et à améliorer la qualité des soins de santé.Cet article examine les principes sous-jacents de cette campagne et sa progression dans le pays.Il met également en évidence l'harmonisation entre les principes de « Choisir avec soin » et ceux de la gestion des antimicrobiens, qui ont en commun des motivations, des difficultés et des possibilités similaires.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".