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Record W2606974999

Evidence Brief: Promouvoir un poids santé par des interventions populationnelles au Canada

2012· article· fr· W2606974999 on OpenAlexaboutno aff
Michael G. Wilson, Emmanuel G. Guindon, Bruce N. Baskerville, François‐Pierre Gauvin

Bibliographic record

VenueMacSphere (McMaster University) · 2012
Typearticle
Languagefr
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Données probantes >> Idées >> ActionMcMaster Health Forum Pour les citoyens intéressés, de même que les penseurs et les acteurs influents, le McMaster Health Forum s'efforce de jouer le rôle de pivot de l'amélioration des résultats de santé grâce à la résolution collective des problèmes.En agissant à un niveau régional/provincial et au niveau national, le Forum met en valeur l'information, réunit les parties prenantes et prépare les dirigeants prêts à mettre en œuvre des actions pour surmonter de façon créative les problèmes de santé urgents.Le Forum agit comme un agent de changement en donnant aux parties prenantes la possibilité d'influencer les agendas gouvernementaux, de mettre en œuvre des mesures mûrement réfléchies et de communiquer efficacement les raisons sous-jacentes à ces mesures.

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)0.021
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.390
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0110.001

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 head0.095
GPT teacher head0.353
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2012
Admission routes1
Has abstractyes

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