Evidence Brief: Promouvoir un poids santé par des interventions populationnelles au Canada
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".