A reanalysis of cancer mortality in Canadian nuclear workers (1956–1994) based on revised exposure and cohort data
Bibliographic record
Abstract
BACKGROUND: A 15-country study of nuclear workers reported significantly increased radiation-related risks of all cancers excluding leukaemia, with Canadian data a major factor behind the pooled results. We analysed mortality (1956-1994) in the updated Canadian cohort and provided revised risk estimates. METHODS: Employment records were searched to verify and revise exposure data and to restore missing socioeconomic status. Excess relative risks per sievert (ERR/Sv) of recorded radiation dose and 95% confidence intervals (CIs) were estimated using Poisson regression. RESULTS: A significant heterogeneity of the dose-response for solid cancer was identified (P=0.02), with 3088 early (1956-1964) Atomic Energy of Canada Limited (AECL) workers having a significant increase (ERR/Sv=7.87, 95% CI: 1.88, 19.5), and no evidence of radiation risk for 42,228 workers employed by three nuclear power plant companies and post-1964 AECL (ERR/Sv=-1.20, 95% CI: <-1.47, 2.39). Radiation risks of leukaemia were negative in early AECL workers and non-significantly increased in other workers. In analyses with separate terms for tritium and gamma doses, there was no evidence of increased risk from tritium exposure. All workers had mortality lower than the general population. CONCLUSION: Significantly increased risks for early AECL workers are most likely due to incomplete transfer of AECL dose records to the National Dose Registry. Analyses of the remainder of the Canadian nuclear workers (93.2%) provided no evidence of increased risk, but the risk estimate was compatible with estimates that form the basis of radiation protection standards. Study findings suggest that the revised Canadian cohort, with the exclusion of early AECL workers, would likely have an important effect on the 15-country pooled risk estimate of radiation-related risks of all cancer excluding leukaemia by substantially reducing the size of the point estimate and its significance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".