PUMA – pooled uranium miners analysis: cohort profile
Bibliographic record
Abstract
OBJECTIVES: Epidemiological studies of underground miners have provided clear evidence that inhalation of radon decay products causes lung cancer. Moreover, these studies have served as a quantitative basis for estimation of radon-associated excess lung cancer risk. However, questions remain regarding the effects of exposure to the low levels of radon decay products typically encountered in contemporary occupational and environmental settings on the risk of lung cancer and other diseases, and on the modifiers of these associations. These issues are of central importance for estimation of risks associated with residential and occupational radon exposures. METHODS: The Pooled Uranium Miner Analysis (PUMA) assembles information on cohorts of uranium miners in North America and Europe. Data available include individual annual estimates of exposure to radon decay products, demographic and employment history information on each worker and information on vital status, date of death and cause of death. Some, but not all, cohorts also have individual information on cigarette smoking, external gamma radiation exposure and non-radiological occupational exposures. RESULTS: The PUMA study represents the largest study of uranium miners conducted to date, encompassing 124 507 miners, 4.51 million person-years at risk and 54 462 deaths, including 7825 deaths due to lung cancer. Planned research topics include analyses of associations between radon exposure and mortality due to lung cancer, cancers other than lung, non-malignant disease, modifiers of these associations and characterisation of overall relative mortality excesses and lifetime risks. CONCLUSION: PUMA provides opportunities to evaluate new research questions and to conduct analyses to assess potential health risks associated with uranium mining that have greater statistical power than can be achieved with any single cohort.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".