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Record W3022377356 · doi:10.7202/1068660ar

Une veille collaborative au service des revues : l’exemple du réseau Mir@bel

2020· article· fr· W3022377356 on OpenAlexvenueno aff
Anabel Vazquez, Sophie Fotiadi

Bibliographic record

VenueDocumentation et bibliothèques · 2020
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Mir@bel est à la fois un site Web, un réservoir partagé d’informations sur les revues et un réseau de plus de 120 professionnels de l’information de différents horizons qui partagent un travail de veille sur les revues et supervisent la mise à jour des données. Le site propose, pour chaque revue, une description bibliographique, des rebonds vers l’environnement numérique de la revue et des accès aux différents types de contenus diffusés (articles, sommaires, résumés). Il reprend de manière automatisée des informations provenant de nombreuses sources, dont les principaux portails de revues francophones en sciences humaines et sociales (Cairn.info, Érudit, OpenEdition Journals et Persée). Pour fonctionner, ce réseau s’appuie sur des méthodes de travail collaboratives, un outil de veille partagé par des bibliothécaires et des professionnels de l’édition, mais également sur les différents processus mis en place pour faciliter un travail participatif. En dix ans de fonctionnement, le réseau a pu expérimenter de nombreuses voies dans cette veille collaborative, que ce soit pour la collecte, la mise à jour, les diffusions de ces données ou la variété des partenariats, facilitant ainsi l’accès aux revues.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.805
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.013
Science and technology studies0.0000.000
Scholarly communication0.0170.047
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.160
GPT teacher head0.357
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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