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Record W4406694030 · doi:10.46747/cfp.7101e19

Améliorer les rapports de recherche en soins primaires

2025· article· fr· W4406694030 on OpenAlexaffvenueabout
Nicholas Pimlott

Bibliographic record

VenueCanadian Family Physician · 2025
Typearticle
Languagefr
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsLibrary sciencePolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

En ce début d’année 2025, Le Médecin de famille canadien (MFC) ajoute la Liste de vérification des éléments de rapport d’études en soins primaires établis par consensus (ÉRÉSPC) aux outils de référence pour les auteurs de la revue et les pairs examinateurs. Quels sont les ÉRÉSPC et

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)0.362
metaresearch head score (Gemma)0.610
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.638
Threshold uncertainty score0.787

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3620.610
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0100.007
Science and technology studies0.0110.008
Scholarly communication0.0210.018
Open science0.0070.019
Research integrity0.0100.017
Insufficient payload (model declined to judge)0.0220.008

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 head0.289
GPT teacher head0.493
Teacher spread0.205 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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
Published2025
Admission routes3
Has abstractyes

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