Lung Cancer Among Firefighters
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
OBJECTIVES: The aim of this study was to explore lung cancer risk among firefighters, with adjustment for smoking. METHODS: We used pooled information from the SYNERGY project including 14 case-control studies conducted in Europe, Canada, New Zealand, and China, with lifetime work histories and smoking habits for 14,748 cases of lung cancer and 17,543 controls. We estimated odds ratios by unconditional logistic regression with adjustment for smoking and having ever been employed in a job known to present an excess risk of lung cancer. RESULTS: There was no increased lung cancer risk overall or by specific cell type among firefighters (n = 190), neither before nor after smoking adjustment. We observed no significant exposure-response relationship in terms of work duration. CONCLUSIONS: We found no evidence of an excess lung cancer risk related to occupational exposure as a firefighter.
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 | 0.000 | 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) | 0.003 | 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