Indoor radon survey in Whitehorse, Canada, and dose assessment
Bibliographic record
Abstract
Abstract Radon-222 ( 222 Rn) and its decay products are the primary sources of a population’s exposure to background ionizing radiation. Radon decay products are the leading cause of lung cancer for non-smokers and the second leading cause of lung cancer after smoking for smokers. A community-driven long-term radon survey was completed in 232 residential homes in different subdivisions of Whitehorse, the capital of the Yukon, during the heating season from November to April in 2016–2017 and in 2017–2018. Radon concentrations were measured in living rooms and bedrooms on ground floors. The arithmetic and geometric means of indoor radon activity concentrations in different subdivisions of Whitehorse ranged from 52 ± 0.6 Bq m −3 and 37 ± 2.3 Bq m −3 in the Downtown area of Whitehorse to 993.0 ± 55.0 Bq m −3 and 726.2 ± 2.4 Bq m −3 in Wolf Creek. Underlying geology and glacial surfaces may partly explain these variations of indoor radon concentrations in subdivisions of Whitehorse. A total of 78 homes (34.0%) had radon concentrations higher than 100 Bq m −3 , 47 homes (20.5%) had concentrations higher than 200 Bq m −3 and 33 homes (14.4%) had concentrations higher than 300 Bq m −3 . The indoor radon contribution to the annual effective inhalation dose to residents ranged from 3.0 mSv in the Downtown area to 51.0 mSv in Wolf Creek. The estimated annual average dose to adults in Whitehorse, Yukon, is higher than the world’s average annual effective dose of 1.3 mSv due to the inhalation of indoor radon. The annual radon inhalation effective dose was assessed using radon measurements taken during winter; hence the assessed dose may be overestimated. Cost-efficient mitigation methods are available to reduce radon in existing buildings and to prevent radon entry into new buildings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".