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Record W4298373767

LE « MONTREAL MODEL » : ENJEUX DU PARTENARIAT RELATIONNEL ENTRE PATIENTS ET PROFESSIONNELS DE LA SANTÉ

2015· preprint· fr· W4298373767 on OpenAlexaffabout
Marie‐Pascale Pomey, Luigi Flora, Philippe Karazivan, Vincent Dumez, Paule Lebel, Marie‐Claude Vanier, Béatrice Débarges, Nathalie Clavel, Emmanuelle Jouet

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2015
Typepreprint
Languagefr
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsGeneral partnershipBusiness
DOInot available

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.489
Threshold uncertainty score0.983

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0070.005
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0340.003

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 head0.032
GPT teacher head0.338
Teacher spread0.306 · 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 designQualitative
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
Published2015
Admission routes2
Has abstractyes

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