MétaCan
Menu
Back to cohort
Record W2915353085 · doi:10.7202/1055291ar

Traitement des acquisitions et du catalogage par ordinateur (TACØ)

2019· article· fr· W2915353085 on OpenAlexaffvenueabout
Richard Boivin, Michel Fortin, Michel Jacob

Bibliographic record

VenueDocumentation et bibliothèques · 2019
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

TACØ, système modulaire de traitement des acquisitions et du catalogage par ordinateur, permettra à la bibliothèque de l’Université du Québec à Trois-Rivières, d’ici trois ans, de gérer automatiquement ses différents procédés de collecte, d’organisation et de contrôle de ses documents. Le premier module est opérationnel depuis août 1976 : il assume les opérations de catalogage et d’indexation, assurant ainsi une zone d’échange avec BADADUQ, système collectif de repérage de la documentation disponible dans les bibliothèques et centres de documentation de l’Université du Québec. Le deuxième module dont l’analyse fonctionnelle est terminée, sera développé au cours de l’année académique 1976/1977; il comprendra les opérations de collecte des documents et de gestion comptable. Suivra immédiatement une troisième phase de développement orientée vers le contrôle de la circulation et de l’utilisation des collections. L’expertise acquise au cours du développement et de l’implantation du premier module de ce projet multidisciplinaire a été significative et encourageante pour la poursuite du plan global.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0030.001
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.008

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 head0.110
GPT teacher head0.347
Teacher spread0.238 · 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

Citations0
Published2019
Admission routes3
Has abstractyes

Explore more

Same venueDocumentation et bibliothèquesSame topicCultural Insights and Digital ImpactsFrench-language works237,207