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Des ebooks dans sa poche : projet de valorisation de la collection numérique de la Bibliothèque de l’UNIGE

2018· article· fr· W2918057511 on OpenAlexaff
Pablo Iriarte, Aurélie Vieux, Marc Meury

Bibliographic record

VenueRevue électronique suisse de science de l information (RESSI) · 2018
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.002
Scholarly communication0.0090.007
Open science0.0010.007
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.008

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.

Opus teacher head0.054
GPT teacher head0.314
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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