Incomplete data on the Canadian cohort may have affected the results of the study by the International Agency for Research on Cancer on the radiogenic cancer risk among nuclear industry workers in 15 countries
Bibliographic record
Abstract
In 1995 the International Agency for Research on Cancer (IARC) completed a study that involved nuclear workers from facilities in the USA, UK and Canada. The only significant, though weak, dose-related associations found were for leukaemia and multiple myeloma. The results for the Canadian cohort, which comprised workers from the facilities of Atomic Energy of Canada Limited (AECL), were compatible with those for the other national cohorts. In 2005, IARC completed a further study, involving nuclear workers from 15 countries, including Canada. In these results, the dose-related risk for leukaemia was not significant but the prominent finding was a statistically significant excess relative risk per sievert (ERR Sv(-1)) for 'all cancers excluding leukaemia'. Surprisingly, the risk ascribed to the Canadian cohort for all cancers excluding leukaemia, driven by the AECL sub-cohort, was significantly higher than the risk estimate for the 15-country cohort as a whole. We have attempted to identify why the results for the AECL cohort were so discrepant and had such a remarkable influence on the 15-country risk estimate. When considering the issues associated with data on the AECL cohorts and their handling, we noted a striking feature: a major change in outcome of studies that involved Canadian nuclear workers occurred concomitantly with the shift to when data from the National Dose Registry (NDR) of Canada were used directly rather than data from records at AECL. We concluded that an important contributor to the considerable upward shift in apparent risk in the 15-country and other Canadian studies that have been based on the NDR probably relates to pre-1971 data and, in particular, the absence from the NDR of the person-years of workers who had zero doses in the calendar years 1956 to 1970. Our recommendation was for there to be a comprehensive evaluation of the risks from radiation in nuclear industry workers in Canada, organisation by organisation, in which some of the anomalies that we have identified might be addressed.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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".