An experimental investigation of tobacco smoke pollution in cars
Bibliographic record
Abstract
INTRODUCTION: Tobacco smoke pollution (TSP) has been identified as a serious public health threat. Although the number of jurisdictions that prohibit smoking in public places has increased rapidly, just a few successful attempts have been made to pass similar laws prohibiting smoking in cars, where the cabin space may contribute to concentrated exposure. In particular, TSP constitutes a potentially serious health hazard to children because of prolonged exposure and their small size. METHODS: The present study investigated the levels of TSP in 18 cars via the measurement of fine respirable particles (<2.5 microns in diameter or PM(2.5)) under a variety of in vivo conditions. Car owners smoked a single cigarette in their cars in each of five controlled air-sampling conditions. Each condition varied on movement of the car, presence of air conditioning, open windows, and combinations of these airflow influences. RESULTS: Smoking just a single cigarette in a car generated extremely high average levels of PM(2.5): more than 3,800 microg/m3 in the condition with the least airflow (motionless car, windows closed). In moderate ventilation conditions (air conditioning or having the smoking driver hold the cigarette next to a half-open window), the average levels of PM(2.5) were reduced but still at significantly high levels (air conditioning = 844 microg/m3; holding cigarette next to a half-open window = 223 microg/m3). DISCUSSION: This study demonstrates that TSP in cars reaches unhealthy levels, even under realistic ventilation conditions, lending support to efforts occurring across a growing number of jurisdictions to educate people and prohibit smoking in cars in the presence of children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".