0384 Endotoxin exposure and lung disease in sawmill workers: a cohort study
Bibliographic record
Abstract
Objectives Previous studies have linked endotoxin exposure with increased risk of COPD, but a decreased risk for lung cancer. We examined these associations in a cohort of British Columbia (BC) sawmill workers followed between 1950 and 1995. Methods The cohort comprised all male production and maintenance workers (n=25,685) at 14 BC sawmills employed for at least one year between 1950 and 1995. Lung cancer cases were identified through the provincial cancer registry, and COPD cases through the provincial hospital discharge data. We assigned cumulative endotoxin exposure for each subject based using a job-exposure matrix built on measurement data obtained at 4 of the study mills. Subjects were assigned to exposure quintile groups for analysis (groups between <1.5 ng/m3 and >14.7 ng/m3), and adjusted risk estimates for each group were calculated using Poisson regression, controlling for potential confounders (smoking that was indirectly addressed). Results Relative risk of lung cancer for highest exposed group was 0.73 (95% CI 0.55–0.98) compared to the reference group, with a slight trend of decreasing risk with increasing endotoxin exposure. Relative risk for COPD in the highest exposed group was 1.9 (95% CI of 0.95–3.70) compared to the reference group, with a slightly increasing trend with increasing endotoxin exposure. Results did not change when different lag times were examined. Conclusion Our findings of a protective effect for endotoxin exposure and lung cancer, and a positive association between endotoxin and COPD are consistent with previous studies, but at lower exposure levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".