Occupational risk factors for renal cell carcinoma in Montreal
Bibliographic record
Abstract
BACKGROUND: Little is known about the role of workplace exposures on the risk of renal cell cancer. METHODS: A population-based case-control study was undertaken in Montreal to assess the association between hundreds of occupational circumstances and several cancer sites, including the kidney. A total of 142 male patients with pathologically confirmed renal cell carcinoma, 1900 controls with cancer at other sites and 533 population-based controls were interviewed. Detailed job histories and relevant data on potential confounders were obtained. A group of chemists-hygienists evaluated each job reported and translated them into a history of occupational exposures using a checklist of 294 substances. Multivariate logistic regression models using either population, cancer controls, or a pool of both groups were used to estimate odds ratios. RESULTS: There were some indications of excess risks among printers, nursery workers (gardening), aircraft mechanics, farmers, and horticulturists, as well as in the following industries: printing-related services, defense services, wholesale trade, and retail trade. Notwithstanding the low precision of many of the odds ratio estimates, the following workplace exposures showed some evidence of excess risk: chromium compounds, chromium (VI) compounds, inorganic acid solutions, styrene-butadiene rubber, ozone, hydrogen sulphide, ultraviolet radiation, hair dust, felt dust, jet fuel engine emissions, jet fuel, aviation gasoline, phosphoric acid and inks. CONCLUSIONS: For most of these associations there exist no, or very little, previous data. Some associations provide suggestive evidence for further studies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".