Développer un service de veilles informationnelles en santé et services sociaux
Bibliographic record
Abstract
Dans les cinq dernières années, la bibliothèque du Centre intégré de santé et de services sociaux (CISSS) de Lanaudière a entrepris de systématiser et de mettre en ligne ses services afin de répondre aux nouveaux besoins de l’organisation. L’offre de services de veilles informationnelles a été révisée en entier afin de s’adapter à ces nouvelles réalités. De veilles spécialisées, les veilles informationnelles sont devenues thématiques. Les processus, quasi entièrement faits manuellement, ont été renouvelés et automatisés pour pallier aux contraintes de ressources et de temps. C’est l’outil Kentika Press qui a été choisi pour enregistrer les fils RSS et créer les bulletins de veilles. Plus d’utilisateurs peuvent désormais bénéficier des services de veilles informationnelles et les premières évaluations du projet sont encourageantes.
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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.013 |
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".