Des ebooks dans sa poche : projet de valorisation de la collection numérique de la Bibliothèque de l’UNIGE
Bibliographic record
Abstract
La valorisation des ressources en ligne, coûteuses et invisibles dans les rayons des bibliothèques, se fait souvent manuellement avec un grand nombre d’étapes chronophages nécessitant des compétences techniques. En 2017, la Bibliothèque de l’Université de Genève a mis sur pied un groupe de travail dont l’objectif est d’harmoniser les pratiques de promotion de leurs collections numériques, notamment les ebooks. Ce projet a abouti à la création de l’Application de valorisation numérique “Avalon”, qui simplifie le processus de création des supports de valorisation (collecte de métadonnées et d’images de couverture, création des URLs raccourcis et QR-codes) tout en respectant la charte graphique institutionnelle. L’accès aux ebooks est simplifié grâce à la lecture des QR-codes, fonctionnalité intégrée à l’application UNIGE mobile, et l’affichage des informations sur une page Web intermédiaire. L’usager peut ainsi littéralement “mettre un ebook dans sa poche”. Cet article a pour objectif de présenter le contexte du projet, la méthodologie employée, le fonctionnement d’Avalon et de proposer un retour d’expérience sur ce projet. The promotion of online resources, which are expensive and invisible on the library shelves, is often done manually with a lot of time-consuming steps requiring technical skills. In 2017, the Geneva University Library set up a working group whose objective is to harmonize the promotion practices of their digital collections, particularly e-books. This project has led to the creation of the digital resources promotion application “Avalon”, which optimizes the process of creating promotional materials (collection of metadata and cover images as well as the creation of shortened URLs and QR-codes) respecting the institutional visual identity. Access to ebooks is simplified by scanning the QR-codes, feature included in the mobile UNIGE application, and displaying the information on an intermediate web page. The user can literally “put an ebook in his pocket”. This article aims to present the context of the project, the methodology, the functionalities of Avalon and to provide experience feedback.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".