Occupational Exposures and Lung Cancer Risk—An Analysis of the CARTaGENE Study
Bibliographic record
Abstract
OBJECTIVE: To determine the associations between prevalent occupational agents and lung cancer risk. METHODS: A case-cohort design (ncases= 147; nsub-cohort= 1,032) was nested within the CARTaGENE prospective cohort study. The Canadian Job Exposure Matrix was used to determine the probability of exposure to 27 agents in participants' longest-held jobs. Multivariable logistic regression with robust variance estimators was used to determine the associations between each agent and lung cancer risk while adjusting for established lung cancer risk factors. RESULTS: Increased lung cancer risk was observed among those exposed to ashes, calcium sulfate, formaldehyde, cooking fumes, alkanes, aliphatic aldehydes, and cleaning agents. Lower lung cancer risk was found among participants exposed to carbon monoxide and polycyclic aromatic hydrocarbons from petroleum. CONCLUSION: Our findings support the role of several occupational agents, for which we have limited knowledge, in contributing to lung cancer risk.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".