Assessment of validity of self-reported smoking status.
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.
Bibliographic record
Abstract
BACKGROUND: Cigarette smoking is associated with adverse health effects, including cancer, respiratory illness, heart disease and stroke. National data on smoking prevalence often rely on self-reports. This study assesses the validity of self-reported cigarette smoking status among Canadians. DATA AND METHODS: Data are from the 2007 to 2009 Canadian Health Measures Survey, a nationally representative cross-sectional survey of 4,530 Canadians aged 12 to 79. The survey included self-reported smoking status and a measure of urinary cotinine, a biomarker of exposure to tobacco smoke. The prevalence of cigarette smoking was calculated based on self-reports and also on urinary cotinine concentrations. RESULTS: Compared with estimates based on urinary cotinine concentration, smoking prevalence based on self-report was 0.3 percentage points lower. Sensitivity estimates (the percentage of respondents who reported being smokers among those classified as smokers based on cotinine concentrations) were similar for males and females (more than 90%). Although sensitivity tended to be lower for respondents aged 12 to 19 than for those aged 20 to 79, the difference did not attain statistical significance. INTERPRETATION: Accurate estimates of the prevalence of cigarette smoking among Canadians can be derived from self-reported smoking status data.
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 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 | 0.000 |
| 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) | 0.000 | 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 it