Cancer incidence and mortality from exposure to radon progeny among Ontario uranium miners
Bibliographic record
Abstract
OBJECTIVES: The study objectives were to extend the follow-up of the Ontario uranium miners cohort, one of the largest cohorts of uranium miners with low cumulative exposures, to examine the relationship between radon exposure and lung cancer mortality and, for the first time incidence, and address gaps in the literature, including dose-response relationship between radon exposure and other cancer sites, and non-cancer mortality. METHODS: The cohort of mine and mill workers was created using data from Canada's National Dose Registry and the Ontario Mining Master File. The follow-up for the cohort was recently extended for mortality (1954-2007) and for the first time includes cancer incidence (1969-2005). The Poisson regression was used to estimate relative risks (RR) and excess relative risks (ERR) and their 95% CIs with levels of cumulative radon exposure. RESULTS: The cohort consisted of 28 546 male miners with a mean cumulative radon exposure of 21.0 working level months (WLM). An increased risk of lung cancer and a dose-response relationship was observed with cumulative radon exposure. Miners exposed to >100 WLM demonstrated a twofold increase in the risk of lung cancer incidence (RR=1.89, CI 1.43 to 2.50) compared with the non-exposed group, and a linear ERR of 0.64/100 WLM (CI 0.43 to 0.85), with similar results observed for mortality. No association was observed for other cancer sites (stomach, leukaemia, kidney and extrathoracic airways) or non-cancer sites (cardiovascular diseases) with increasing cumulative exposure to radon. CONCLUSIONS: These findings suggest no increased risk of cancer sites other than lung or non-cancer mortality from relatively low cumulative exposure to radon.
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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 | 0.000 | 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 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".