Measuring Tobacco Smoke Exposure Among Smoking and Nonsmoking Bar and Restaurant Workers
Bibliographic record
Abstract
PURPOSE: This study assesses the validity of hair nicotine as a biomarker for secondhand smoke (SHS) exposure. Although most biomarkers of tobacco-smoke exposure have a relatively short half-life, hair nicotine can measure several months of cumulative SHS exposure. DESIGN: A cross-sectional study of hospitality-industry workers. METHOD: Hair samples were obtained from 207 bar and restaurant workers and analyzed by the reversed-phase high-performance liquid chromatography with electrochemical detection (HPLC-ECD) method. Self-reported tobacco use and sources of SHS exposure were assessed. FINDINGS: Higher hair-nicotine levels were associated with more cigarettes smoked per day among smokers and a greater number of SHS-exposure sources among nonsmokers. Number of SHS exposure sources, gender, number of cigarettes smoked per day, and type of establishment predicted hair-nicotine levels. DISCUSSION: Hair nicotine is a valid measure of SHS exposure. It may be used as an alternative biomarker to measure longer term SHS exposure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".