Identification of Occupational Cancer Risks In British Columbia: A Population-Based Case–Control Study of 1129 Cases of Bladder Cancer
Bibliographic record
Abstract
OBJECTIVE: We collected information on lifetime occupational histories, smoking, and alcohol consumption from 15,463 incident cancer cases. Occupational risk factors for bladder cancer are presented in this report. METHOD: A matched case-control design was used. All cases were diagnosed with bladder cancers, with controls being internal controls consisting of all other cancer sites, excluding lung and unknown primary. Data were analyzed using conditional logistic regression for matched sets data and the likelihood ratio test. RESULTS: Excess bladder cancer risks was observed in a number of occupation and industries, particularly those involving exposure to metals, including aluminum, paint and solvents, polycyclic aromatic hydrocarbons, diesel engine emissions, and textiles. CONCLUSIONS: The results of our study are in line with those from the literature and further suggest that exposure to silica and to electromagnetic fields may carry an increased risk of bladder cancer.
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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) | 0.001 | 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) | 0.002 | 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 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".