Potential Influence of Sewage Phosphorus and Wet and Dry Deposition Detected in Fish Collected in the Athabasca River North of Fort McMurray
Bibliographic record
Abstract
The health of fish is a primary indicator of ecosystem response in the Oil Sands Region of northeastern Alberta. However, industrial activity is accompanied by other stressors, such as the discharge of sewage, municipal activity, forest fires, and natural weathering and erosion of bitumen. To combat the spatial confounding influences, we examined white sucker (Catostomus commersonii) captured in the Athabasca River at sites over time (2011–2019) and included covariates to account for the possible sources of influence. The analyses suggest spatially heterogeneous influences of natural factors on fish, such as discharge and air temperature, but also the influence of sewage phosphorus and precipitation. Among the stressors examined here, precipitation may be the most complex and may include a mixture of sources including inputs from tributaries, urban activity, industrial development, and forest fires. Although suggestive, the attribution of variance and detection of changes are affected by sample sizes in some years; these analyses may have missed effects or misspecified important relationships, especially in males. Despite these limitations, the analyses suggest potential differences may be associated with precipitation and highlight the need to integrate robust information on known and suspected stressors in future monitoring of aquatic ecosystems in the oil sands region and beyond.
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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 | 0.000 | 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".