RADON AND LUNG CANCER RISK: AN EXTENSION OF THE MORTALITY FOLLOW-UP OF THE NEWFOUNDLAND FLUORSPAR COHORT
Bibliographic record
Abstract
Radon is a well-recognized cause of lung cancer, and studies of underground miners have provided invaluable insights on the mechanisms of radon carcinogenesis. Given the dramatic decreases in occupational exposures and the latent interval between the time of exposure and the development of lung cancer, continued follow-up of these cohorts is needed to address uncertainties in risk estimates. Here, we report on the relationship between radon and lung cancer mortality in a cohort of 1,742 Newfoundland fluorspar miners between 1950 and 2001; follow-up has been extended 11 y from previous analyses. The standardized mortality ratio (SMR) was used to compare the mortality experience of the cohort to similarly aged Newfoundland males. Poisson regression methods were used to characterize the radon-lung cancer relationship with respect to: age at first exposure, attained age, time since last exposure, interactions with cigarette smoking, and exposure rate. In total, 191 lung cancers were observed among underground miners (SMR = 3.09; 95% CI = 2.66, 3.56). ERR/WLMs decreased with attained age and time since last exposure. An inverse dose-rate effect was observed, while age at first exposure was not associated with lung cancer risk. An important strength of this study is that the effects of gamma radiation, thoron, and radioactive dust, common exposures in other miner studies, can be ruled out because the source of radon was from water running through the mine. However, the results should be interpreted cautiously due to uncertainties associated with the estimation of radon exposure levels before ventilation was introduced into the mine, and the relatively small number of lung cancer deaths that precluded joint modeling of multiple risk factors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".