Les programmes d'éducation à la santé semblent efficaces pour bien vieillir
Bibliographic record
Abstract
Pour réussir son vieillissement en restant en bonne santé et autonome le plus longtemps possible, un mode de vie sain évitant les facteurs de risque des grandes pathologies doit être adopté précocement et maintenu. Il n’est toutefois jamais trop tard pour bien faire. Modifier des comportements même tardivement peut s’avérer bénéfique pour la santé. Les différents travaux résumés dans cet article montrent que les personnes qui réduisent leurs facteurs de risque vieillissent en meilleure santé, retardent la survenue de la dépendance et changent leur mode de consommation de soins. Ces actions de promotion visant à améliorer les comportements positifs peuvent être ciblées sur certains aspects de la santé, tels que la nutrition, l’activité physique, le sommeil, la prise de médicaments ou être intégrées dans des programmes globaux couvrant plusieurs de ces domaines.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".