Exposition des cyclistes à la pollution sonore et atmosphérique à Lyon, France
Bibliographic record
Abstract
L’objectif de cet article est de modéliser l’exposition des cyclistes au bruit et au dioxyde d’azote (NO 2 ) à Lyon (France). Les données primaires (1 095 km), collectées à vélo en février 2019, permettent de construire trois modèles bayésiens (modèles généralisés additifs à effets mixtes avec un terme autorégressif) avec, comme variables dépendantes : le bruit (dB(A)), la concentration de NO 2 (μg/m 3 ) et l’inhalation de NO 2 (μg). Les résultats montrent que les expositions des cyclistes et l’inhalation de NO 2 varient significativement en fonction des types d’axes qu’ils empruntent. Par conséquent, ces deux nuisances urbaines devraient être prises en compte lors de la planification des voies cyclables.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".