Radon and Nonrespiratory Mortality in the American Cancer Society Cohort
Bibliographic record
Abstract
Radon is a known cause of human lung cancer. Previously, the authors observed a significant positive association between mean county-level residential radon concentrations and lung cancer mortality in the Cancer Prevention Study II (CPS-II), a large prospective study of nearly 1.2 million participants recruited in 1982 by the American Cancer Society. There was also a significant positive association with mortality from chronic obstructive pulmonary disease. Because it is unclear whether radon is associated with mortality from other malignant or nonmalignant disease, the authors examined the association between radon and nonrespiratory mortality in the CPS-II. Mean county-level residential radon concentrations (mean = 53.5 (standard deviation: 38.0) Bq/m(3)) were linked to participants by their zip code at enrollment. Cox proportional hazards regression models were used to estimate adjusted hazard ratios and 95% confidence intervals for all-cause (excluding lung cancer and respiratory mortality) and cause-specific mortality associated with radon concentrations. A total of 811,961 participants in 2,754 counties were analyzed, including 265,477 deaths through 2006. There were no clear associations between radon and nonrespiratory mortality in the CPS-II. These findings suggest that residential radon is not associated with any other mortality beyond lung cancer or chronic obstructive pulmonary disease.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".