Bibliographic record
Abstract
La Bibliothèque de l’Assemblée nationale du Québec répond aux demandes d’information et de recherche des différentes communautés parlementaires. À l’automne 2017, le service de la référence de la Bibliothèque a entamé un processus de conception d’un système de gestion des demandes de référence à l’aide d’Ultima, un logiciel de gestion intégrée de l’information. Ce système – implanté officiellement au sein de l’équipe en août 2018 – est devenu une grande source d’information sur les différents publics de la Bibliothèque et a permis à l’institution de mieux servir ses différentes clientèles. Afin que l’expérience de la Bibliothèque profite à d’autres institutions documentaires, cet article explique le processus d’implantation d’un système de gestion des demandes au sein d’un service de la référence, et dévoile le potentiel d’un tel système dans l’acquisition d’une meilleure connaissance des publics et de leurs besoins d’information.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.056 | 0.011 |
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".