Evaluation of occupational radon exposure and comparison with residential radon exposure in Canada—a population-level assessment
Bibliographic record
Abstract
Radon is a naturally occurring radioactive gas and presents everywhere on the Earth at varying concentration in workplaces and at homes. With Canadian labour statistics, time statistics and more than 7600 long-term radon measurements in workplaces, occupational radon exposure is evaluated for all 20 job categories based on North American Industry Classification System. Results are compared with residential radon exposure based on more than 22 000 long-term radon tests conducted in Canadian homes. The average annual effective dose due to radon exposure in workplaces is 0.21 mSv, which is lower than the average annual effective dose of 1.8 mSv from radon exposure at home by a factor of eight. Due to relatively higher radon concentration in residential homes and longer time spent indoors at home, exposure at home contributes to 90% of workers' total radon exposure (on average 1692 h in workplaces and 5852 h at homes). The analysis presented here is based on province-wide average radon exposures in various indoor and outdoor environments. Since the risk of developing lung cancer increases proportionally with increasing radon exposure, this evaluation indicates that on average reduction of radon levels in homes is very important and an effective way to reduce radon-induced lung cancers in Canada.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".