Canadian population risk of radon induced lung cancer: a re-assessment based on the recent cross-Canada radon survey
Bibliographic record
Abstract
Exposure to indoor radon has been determined to be the second leading cause of lung cancer after tobacco smoking. Canadian population risk of radon induced lung cancer was assessed in 2005 with the radon distribution characteristics determined from a radon survey carried out in the late 1970s in 19 cities. In that survey, a grab sampling method was used to measure radon levels. The observed radon concentration in 14,000 Canadian homes surveyed followed a log-normal distribution with a geometric mean (GM) of 11.2 Bq m(-3) and a geometric standard deviation (GSD) of 3.9. Based on the information from that survey, it was estimated that ∼10 % of lung cancers in Canada resulted from indoor radon exposure. To gain a better understanding of radon concentrations in homes across the country, a national residential radon survey was launched in April 2009. In the recent survey, long-term (3 month or longer) indoor radon measurements were made in roughly 14 000 homes in 121 health regions across Canada. The observed radon concentrations follow, as expected, a log-normal distribution with a GM of 41.9 Bq m(-3) and a GSD of 2.8. Based on the more accurate radon distribution characteristics obtained from the recent cross-Canada radon survey, a re-assessment of Canadian population risk for radon induced lung cancer was undertaken. The theoretical estimates show that 16 % of lung cancer deaths among Canadians are attributable to indoor radon exposure. These results strongly suggest the ongoing need for the Canadian National Radon Program. In particular, there is a need for a focus on education and awareness by all levels of government, and in partnership with key stakeholders, to encourage Canadians to take action to reduce the risk from indoor radon exposure.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".