ESTIMATED RISKS OF RADON-INDUCED LUNG CANCER FOR DIFFERENT EXPOSURE PROFILES BASED ON THE NEW EPA MODEL
Bibliographic record
Abstract
Radon is a naturally occurring radioactive gas. When inhaled, radon can cause mutations that lead to lung cancer. Some new epidemiologic studies indicate that indoor radon is a public health problem. The BEIR VI report outlined its preferred two risk models for the combined effects of smoking and exposure to radon progeny, and listed the estimated risk to ever-smokers and never-smokers of both sexes due to lifetime exposure. However, exposures for shorter periods of time are of practical interest since exposure to elevated levels of radon may occur and end at any age. This study aims to produce practical tables of lifetime relative risks for exposures between any two age intervals from 0 to 110, and for various radon concentrations found in homes from 100 to 1,000 Bq m(-3). The calculations are based on the risk model developed recently by U.S. Environmental Protection Agency. The EPA's risk model is a single model that gives risk values midway between those obtained from the two BEIR VI preferred models. The detailed tables provide a clearer view of the age groups at higher risk and the effect of exposure duration. The results will help radiation protection practitioners to better communicate indoor radon risk to members of the public.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".