Bibliographic record
Abstract
Les benzodiazepines sont des molecules largement employees dans les traitements de l’insomnie et de l’anxiete. Leur utilisation est problematique depuis des annees en France, et ce, du fait de leur surconsommation et de leur profil de securite d’emploi particulier. Les nombreuses recommandations emises par les autorites de sante afin de limiter l’usage des benzodiazepines n’aboutissent qu’a de faibles resultats, il convient alors d’etudier et d’envisager de nouvelles possibilites afin de reduire la consommation et de favoriser le bon usage de ces molecules. La deprescription est un processus permettant de reduire voire d’arreter un medicament inapproprie et est particulierement utilisee pour les benzodiazepines dans les pays ayant deja mis en place ce procede, comme le Canada et l’Australie. La deprescription s’inscrit dans un contexte actuel d’evolution du domaine de la pharmacie ou les nouvelles mesures mises en place recemment a l’officine, telles que la conciliation medicamenteuse et la possibilite d’effectuer des bilans de medication, permettent au pharmacien de mettre ses competences pharmaceutiques au service de l’amelioration de la prise en charge du patient.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".