Electron Paramagnetic Resonance Measurements of Lifetime Doses in Teeth of Durham Region Residents, Ontario
Bibliographic record
Abstract
ABSTRACT: The Canadian Nuclear Safety Commission (CNSC) and Ontario Power Generation (OPG) determined the total dose contribution of nuclear power plants in Durham Region populations by analyzing environmental samples from the surrounding areas of both nuclear generating stations (Pickering and Darlington). However, the total doses from the various sources were unknown in Durham Region populations, Ontario. Electron paramagnetic resonance (EPR) dosimetry with tooth enamel has been successfully established as an effective tool for gamma dose assessment for chronic and acute exposures in individuals, groups, or populations to reconstruct the absorbed dose down to 30 mGy. This study collected the extracted teeth from people of different ages in Durham Region, Ontario, and analyzed them using the x-band continuous wave (CW) EPR spectrometer. The total dose rate from the natural and anthropogenic sources was 1.9721 mSv y-1. The anthropogenic dose rate from the various sources was 0.6341 mSv y-1, about 47.39% of the natural background dose (1.338 mSv y-1) in Durham Region, Ontario. The combined anthropogenic doses from these sources were lower than the local background dose in Durham Region and lower than the regulatory annual effective dose limit of 1 mSv y-1 in Canada. Based on these data, this study concluded that the anthropogenic dose contribution was lower than the regulatory limit to the local populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".