Cancer Incidence and Occupational Radiation Exposure Sont et al. ORIGINAL CONTRIBUTIONS First Analysis of Cancer Incidence and Occupational Radiation Exposure Based on the National Dose Registry of Canada
Bibliographic record
Abstract
A cohort study was conducted to investigate the relation between cancer incidence and occupational exposure to ionizing radiation. Records containing dose information from 1951 to 1988 for 191,333 persons were extracted from the National Dose Registry of Canada. The records were linked to the Canadian Cancer Data Base, with incidence data from 1969 to 1988. Standardized incidence ratios were calculated using Canadian cancer incidence rates stratified by age, sex, and calendar year. Excess relative risks were obtained from internally based dose-response analyses. The following significant results were found for males and females combined: a deficit in the standardized incidence ratio for all cancers combined; elevated standardized incidence ratios for thyroid cancer and melanoma; and elevated excess relative risks for rectum, leukemia, lung, all cancers combined, all except lung, and all except leukemia. For males, cancers of the colon, pancreas, and testis also showed significantly elevated excess relative risks. The specific cancer types listed above have been implicated in previous studies on occupational exposure to ionizing radiation, except for testis, colon, and melanoma, while the findings on thyroid cancer from previous studies are inconclusive. The thyroid standardized incidence ratios in this study are highly significant, but further investigation is needed to assess the possibility of association with occupational radiation exposure. Am J Epidemiol 2001;153:309–18. incidence; neoplasms; occupational exposure; radiation
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".