Identifying high-risk workplaces for radon: The role of buildings’ foundations and underground water sources
Bibliographic record
Abstract
OBJECTIVE: Radon, a naturally occurring lung carcinogen, can seep into buildings and expose occupants, including workers. Our aim is to describe radon exposure in various workplaces, identify factors associated with exposure, and highlight levers for preventive action. MATERIAL AND METHODS: Workplaces with an underground or slab-on-grade work area were recruited in four regions of Québec (Central Canada) with high and low potential for radon emissions. Long-term radon samples were taken during the cold season with Alpha Track AT-100 passive dosimeters, deployed by the research team in accordance with Health Canada's Guide for radon measurements in public buildings. RESULTS: There were 354 radon measurements in 57 buildings constructed between 1877 and 2021 (54 workplaces), with on average six measurements (1-28) per workplace during a median of 109 days. Ten buildings had all measurements below the detection limit (15 Bq/m³), and six had at least one measurement above 100 Bq/m³. The highest values recorded were in a fish hatchery (>1500 Bq/m³). Generalized estimating equations revealed that a lowest floor made of materials other than poured concrete, the presence of naturally occurring radioactive material (underground water), and a small building footprint were the most predictive factors of higher concentrations, regardless of the regional radon emission potential. CONCLUSION: In this convenience sample, most workplaces presented radon concentrations well below guidelines. However, the surprise expressed by workplace managers and public health officials regarding high concentrations associated with NORM is evidence of a lack of awareness of the dangers of radon in these environments.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".