Système de recommandation basé sur les notices bibliographiques MARC 21 : étude de cas à Bibliothèque et Archives nationales du Québec (BAnQ)
Bibliographic record
Abstract
Le présent article propose un système de recommandations fondé sur le filtrage des documents associés à des notices bibliographiques MARC 21 et l’historique des emprunts de l’abonné provenant du système intégré de gestion de bibliothèque. L’expérience a été menée en 2017 à Bibliothèque et Archives nationales du Québec. Le taux de précision élevé obtenu lors de la période d’évaluation prouve le potentiel et la faisabilité du système. Les résultats obtenus montrent que l’utilisation d’un système de recommandation adapté aux bibliothèques publiques permet d’améliorer la qualité des services offerts aux usagers avec un minimum d’impact sur les systèmes opérationnels déjà en place.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.028 | 0.047 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".