A cancer incidence and mortality study of Dow Chemical Canada Inc. manufacturing sites
Bibliographic record
Abstract
BACKGROUND: Previously, the mortality was reported in a cohort of male workers at an Ontario chemical plant. AIMS: To expand the cohort and to investigate the mortality and cancer incidence risk among chemical manufacturing sites. METHODS: We followed 5277 men and 1301 women from 1950 to 1999. RESULTS: Employees experienced lower mortality and cancer incidence rates than the general population for several major causes of death, including heart disease, respiratory cancer and many other cancers. There were no cases of angiosarcoma of the liver. We observed a lower mortality rate of prostate cancer [standardized mortality ratio = 0.79, 95% confidence interval (CI) 0.43-1.32], but a higher incidence rate of prostate cancer [standardized incidence ratio (SIR) = 1.22, 95% CI 1.00-1.48]. Among the Sarnia employees, the incidence of pleural neoplasms was increased (5 observed versus 1.48 expected, SIR = 3.37, 95% CI 1.09-7.86). These cancers were included in the 12 deaths with malignant mesothelioma at Sarnia. CONCLUSION: Consistent with the earlier report, lower mortality rates were observed for the major classifications of disease and malignant neoplasms. The higher incidence rates of prostate cancer are not readily explainable but may reflect increased screening among current employees and recent retirees. Past asbestos exposure prior to 1980 is probably a contributor to the deaths due to malignant mesothelioma but is not reflected in lung cancer mortality. We find little indication of any other increased rates of mortality or cancer within the overall workforce of these chemical plants.
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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 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.003 | 0.001 |
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".