Surveillance of cancer risks for firefighters, police, and armed forces among men in a Canadian census cohort
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: Firefighters, police, and armed services may be exposed to hazards such as combustion by-products and shift work. METHODS: The CanCHEC cohort linked 1991 census data to the Canadian cancer registry for follow up. Cox proportional hazards modeling was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate risks for firefighter, police, or armed forces compared to workers in other occupations. RESULTS: The cohort of 1 108 410 men included 4535 firefighters, 10 055 police, and 9165 armed forces. For firefighters, elevated risks were noted for Hodgkin's lymphoma (HR: 2.89, 95%CI: 1.29-6.46), melanoma (HR: 1.67, 95%CI: 1.17-2.37), and prostate cancer (HR: 1.18, 95%CI: 1.01-1.37). Police had elevated risks for melanoma (HR:1.69, 95%CI: 1.32-2.16) and prostate cancer (HR:1.28, 95%CI: 1.14-1.42). No significant associations were found for armed forces workers. CONCLUSIONS: Canadian firefighters, police, and armed services, may be at an increased risk of developing certain cancers. Results suggested that a healthy worker effect may influence risk estimates.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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