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Record W2039883390 · doi:10.1177/1099800407300852

Measuring Tobacco Smoke Exposure Among Smoking and Nonsmoking Bar and Restaurant Workers

2007· article· en· W2039883390 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiological Research For Nursing · 2007
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of British Columbia
FundersCenters for Disease Control and PreventionUniversity of Kentucky
KeywordsNicotineMedicineTobacco smokeEnvironmental healthBiomarkerSecondhand smokeSmokeOccupational exposureCotinineToxicologyInternal medicineWaste managementChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.301
GPT teacher head0.436
Teacher spread0.134 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it