Lung Cancer Risk Among Cooks When Accounting for Tobacco Smoking: A Pooled Analysis of Case-Control Studies From Europe, Canada, New Zealand, and China
Bibliographic record
Abstract
OBJECTIVES: To investigate the risk of lung cancer among cooks, while controlling for smoking habits. METHODS: We used data from the SYNERGY project including pooled information on lifetime work histories and smoking habits from 16 case-control studies conducted in Europe, Canada, New Zealand, and China. RESULTS: Before adjustment for smoking, we observed an increased risk of lung cancer in male cooks, but not in female cooks. After adjusting, there was no increased risk and no significant exposure-response relationship. Nevertheless, subgroup analyses highlighted some possible excess risks of squamous cell carcinoma and small cell carcinoma in female cooks. CONCLUSIONS: There is evidence that lung cancer risks among cooks may be confounded by smoking. After adjustment, cooks did not experience an increased risk of lung cancer overall. The subgroup analyses showing some excess risks among female cooks require cautious interpretation.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".