Faire d’une pierre deux coups : retombées positives d’actions contre les îlots de chaleur urbains
Bibliographic record
Abstract
Pour contrer les ilots de chaleur urbains (ICU), l’Institut national de sante publique du Quebec (INSPQ) a mis en place, en 2009, un programme de subventions. L’objectif de ce programme etait d’ameliorer la sante de la population par le biais de projets de demonstration de mesures efficaces de lutte contre les ICU realises dans plusieurs regions du Quebec. Plus de quarante projets ont ete ainsi finances, visant principalement la vegetalisation d’espaces betonnes et asphaltes. Une evaluation de la qualite de vie des citoyens a ete realisee par le biais de sondages et de questionnaires, dans l’annee qui a suivi la realisation de certains des projets. S’il etait trop tot pour qu’ils percoivent un benefice important en ce qui concerne la baisse de la temperature, puisque les vegetaux n’etaient pas a maturite, l’evaluation a tout de meme montre leur satisfaction des projets realises. Plus encore, des entretiens avec les porteurs de projets ont etabli plusieurs retombees positives sur les communautes, notamment quant a la cohesion sociale, la securite et l’adoption d’habitudes de vie plus saines.
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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 | 0.025 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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.
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".