Characterizing Radon Among Public Buildings and Small/Medium-Sized Businesses in a Canadian Province
Bibliographic record
Abstract
Radon is a naturally occurring radioactive gas that causes lung cancer. It has been measured extensively in homes and mines but research in other workplaces has been limited. The present study examined 453 workplaces in Ontario, Canada, to characterize radon levels. Radon monitors (n = 687) were placed in occupied ground floor and basement workplace locations for a minimum of three months. The radon measurements ranged from <4 to 566 Bq/m3, with a median of 26 Bq/m3, arithmetic mean of 40.2 Bq/m3, and geometric mean of 26.9 Bq/m3. Using the Health Canada and Ontario labor guideline of 200 Bq/m3, 2.5% of participating workplaces had at least one measurement above this level; 7.2% were above the World Health Organization guideline. Workplaces were also asked to fill out questionnaires to identify possible determinants of exposure. Radon levels varied significantly based on municipality and background radon zone, highlighting the importance of geography in influencing radon levels. Radon levels also varied significantly based on window-opening behavior, business access type, the presence of an elevator, air conditioning, additions to the building, and cracks and/or gaps in the foundation/wall and around drains, indicating building characteristics with some influence on air circulation may impact overall radon levels.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| 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".