Effects of uranium mining and milling on benthic invertebrate communities in the Athabasca Basin of Northern Saskatchewan
Bibliographic record
Abstract
Aquatic environments downstream of uranium operations (mining/milling) in Northern Saskatchewan are exposed to a variety of chemical and physical disturbances. There is extensive regulatory documentation of monitoring and effects assessments for modern uranium operations, though little is available in the scientific literature. The reference condition approach was used to predict expected benthic invertebrate community metrics for unexposed and exposed lakes. This approach was used to identify impacted communities that differed significantly from expected natural regional compositions. The number of taxa at the lowest practical level (taxon richness) downstream of approximately half of the uranium operations’ effluent release points was lower compared to the number of taxa observed in reference conditions. The taxon richness residuals were strongly correlated with about half of the measured concentrations of sediment contaminants and always negatively, such that richness was lower in lakes with higher concentrations of metals or radionuclide activities in the sediments. This was consistent for both reference and exposure lakes, implying a natural background influence of some metals and radionuclides on taxon richness. This exercise produced models that can be used by practitioners in the north of Saskatchewan in the design and delivery of monitoring programs not only for uranium mines, but for regional cumulative effects studies in support of sustainable resource planning and management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".