Vulnerability of Canadian aquatic ecosystems to nuclear accidents
Bibliographic record
Abstract
Sr), but have not been used to make predictions of radiological risk from nuclear accidents under variable environmental conditions on broad geographical scales. In this paper, we first present models for predicting the bioaccumulation of cesium and strontium by aquatic biota based on ambient concentrations of dissolved potassium and calcium, respectively, and then test these models using independent data from aquatic ecosystems at Canadian nuclear sites. Secondly, models yielding the best predictions across a wide range of input parameters were selected to estimate bioaccumulation factors (BAFs) for cesium and strontium in aquatic ecosystems across Canada, using trophic level of organisms and dissolved potassium for cesium and calcium concentrations for strontium as predictor variables, and presented as contour maps of radiological risk. The models show that risk from bioaccumulation of cesium and strontium can vary by several orders of magnitude depending on site-specific environmental conditions and trophic ecology. Overall, our results suggest that single-parameter approaches taken by regulatory standards may either over- or under-predict radiological risk at many locations, and are thus not readily suitable to inform siting decisions for new nuclear developments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".