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Record W2523163376 · doi:10.7202/1029333ar

Les revues professionnelles en sciences de l’information au Québec

2015· article· fr· W2523163376 on OpenAlexaffvenueabout
Louise Gagnon-Arguin

Bibliographic record

VenueDocumentation et bibliothèques · 2015
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceDocumentationArtComputer science

Abstract

fetched live from OpenAlex

Trois revues professionnelles sont publiées au Québec. Il s’agit des revues Archives (Association des archivistes du Québec, 1969), Argus (Corporation des bibliothécaires professionnels du Québec, 1971) et Documentation et bibliothèques (Association pour l’avancement des sciences et des techniques de la documentation, 1973). Après avoir dressé le portrait général de chacune d’elles, l’auteure considère ici les thèmes abordés et les auteurs des articles depuis plus de trente ans et elle souligne les défis à relever pour en assurer la continuité.

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)0.008
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.016
Science and technology studies0.0110.006
Scholarly communication0.0120.005
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0360.004

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 head0.251
GPT teacher head0.428
Teacher spread0.178 · 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.

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

Citations3
Published2015
Admission routes3
Has abstractyes

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