Low-level radon exposure and lung cancer in the Pooled Uranium Miners Analysis (PUMA)
Bibliographic record
Abstract
BACKGROUND AND AIM: Radon, a ubiquitous gas, and its progeny are a leading environmental and occupational cause of lung cancer. To better inform radiation protection standards by estimating risk, we assembled an international cohort study of workers employed in uranium mining in Canada, the Czech Republic, France, Germany, and the United States. METHODS: We focus on miners employed during the more contemporary period of the uranium mining industry when radon exposures tended to be comparatively low, and individual exposure data are available. A cohort of 56,614 male uranium miners first employed in 1960 or later was assembled and followed to ascertain causes of death. Estimates of excess relative rate (ERR) per working level month (WLM) of cumulative radon progeny exposure for mortality from lung cancer were derived by internal Poisson regression. RESULTS:In the follow-up period a total of 1217 lung cancer deaths occurred, accumulating 1.9 million person-years at risk. The relative rate of lung cancer increased in a linear fashion with cumulative exposure to radon progeny, lagged 5 years (ERR/100 WLM=1.34; 95% CI: 0.89, 1.89). Attained age was a clear modifier of this association, showing a decrease in ERR/WLM with increasing attained age. Further potential modifiers are age at exposure or time since exposure and exposure rate. CONCLUSIONS:PUMA provides the most precise and informative estimates to-date of the association between low-level exposure to radon progeny and lung cancer mortality. The results strengthen the basis for radiation protection standards for radon and its progeny. KEYWORDS: Ionizing radiation, Occupational exposures, Risk assessment,International collaboration
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".