Secondhand Smoke in Pennsylvania Casinos: A Study of Nonsmokers' Exposure, Dose, and Risk
Bibliographic record
Abstract
OBJECTIVES: I assessed air pollution, ventilation, and nonsmokers' risk from secondhand smoke (SHS) in Pennsylvania casinos exempted from a statewide smoke-free workplace law. METHODS: I measured respirable suspended particles (RSPs), particulate polycyclic aromatic hydrocarbons (PPAHs), and carbon dioxide inside and outside casinos; measured changes in patrons' urine cotinine after casino visits; and assessed SHS impact on workers and patrons, using exposure-response models, air quality standards, and odor and irritation thresholds. RESULTS: PPAH and RSP concentrations in casinos were, on average, 4 and 6 times, respectively, that of outdoor levels despite generous ventilation and low smoking prevalence. SHS infiltrated into nonsmoking gaming areas. Patrons' urine cotinine increased 1.9 ng/mL on average after about 4-hour visits. CONCLUSIONS: SHS-induced heart disease and lung cancer will cause an estimated 6 Pennsylvania casino workers' deaths annually per 10,000 at risk, 5-fold the death rate from Pennsylvania mining disasters. Casinos should not be exempt from smoke-free workplace laws.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".