Concentrations of Metals in Fishes from the Athabasca and Slave Rivers of Northern Canada
Bibliographic record
Abstract
There is growing concern about possible effects of exploitation of the Alberta Oil Sands on the ambient environment, including possible effects on populations of fishes in the Athabasca River and farther downstream in Lake Athabasca and the Slave River. In the present study, concentrations of metals in dorsal muscle tissue of 5 fish species-goldeye, northern pike, walleye, whitefish, and burbot-from the Slave, Peace, and Athabasca Rivers were quantified. A suite of 25 metals including As, Hg, Se, Tl, and V was analyzed. Most metals exhibited no significant variations in concentration among locations. Concentrations of 5 metals, As, Hg, Se, Tl, and V, revealed significant variations among locations and were of sufficient magnitude to be of interest. Concentrations of Hg did not vary significantly among locations; however, because it was detected at concentrations of concern and the use of the selected fishes was a local source of food for humans and pets, it was of interest. Concentrations of As, Se, Tl, and V in dorsal muscle of certain fishes in the farthest downstream sites on the Slave River were greater than those in the same tissues and species in the farther upstream sites on the Peace and Athabasca Rivers. This phenomenon was most prevalent with Tl and to a lesser extent with As and Se. Nevertheless, concentrations were not of concern for the health of human consumers. Although metals did not appear to be increased in fish in the Alberta Oil Sands region in the present study, further research is needed to understand the potential impacts. Environ Toxicol Chem 2020;39:2180-2195. © 2020 SETAC.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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".