Bibliographic record
Abstract
Radionuclides were first discovered in the late 1800s, and artificial (anthropogenic) radionuclides in the 1930s. Since then, this group of substances has been increasingly incorporated into various peaceful and non-peaceful applications across Canada and the world, bringing with it both advanced technological and medical benefits, and public concern about the dangers from radiation exposure. As such, a breadth of research on, and monitoring of, radionuclides in the Canadian environment has been generated, the results of which span decades. However, a recent comprehensive review of these is not readily available. This study aims to fill this gap by synthesizing available literature from the last 30 years on the Canadian state and provenance of radionuclide contamination to better understand the context of overall sources and status of contamination. The findings indicate that while regional and temporal variations exist, on average, routine radionuclide exposure in Canada is generally attributed mainly to natural sources and fallout from historical nuclear weapons testing and nuclear accidents (including the Chernobyl and Fukushima power plant accidents) and to a smaller degree to emissions from nuclear facilities, including active and historical uranium mines and mills, nuclear research facilities, and nuclear power plants. Levels of anthropogenic radionuclides in the Canadian environment have declined since the initial cessation of nuclear weapons testing in the 1960s and are generally below guidelines protective of human health. On the national scale, present-day nuclear sector facilities do not appear to be a significant source of routine anthropogenic, nor technically-enhanced naturally occurring radionuclide exposure, though local scenarios may vary. These findings contribute context for evaluating the sustainable management of nuclear technologies, radioactive materials and waste in Canada and globally, in line with UN Sustainable Development Goal 12 and target 12.4: responsible management of chemicals and waste.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.027 | 0.046 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".