Population impacts in white sucker (<i>Catostomus commersonii</i>) exposed to oil sands–derived contaminants in the Athabasca River
Bibliographic record
Abstract
Biological and chemical endpoints were measured in white sucker collected downstream of Athabasca oil sands developments (AB, Canada) and compared with those at Calling Lake (AB, Canada), a reference location upstream of the Athabasca oil sands deposit. Naphthenic acid concentrations were also measured at 14 sites in the Athabasca River watershed. Concentrations of naphthenic acids were elevated in tributaries adjacent to oil sands mining developments. Tributary naphthenic acid profiles were more similar to aged oil sands process water than samples from the Athabasca River, suggesting an influence of tailings in the tributaries. White sucker showed higher energy storage in the Athabasca River as indicated by significantly higher condition and liver size. White sucker were not investing that energy into reproductive effort as measured by gonad size and fecundity, which were significantly reduced relative to the reference location. White sucker showed increased exposure to polycyclic aromatic hydrocarbons as indicated by hepatic cytochrome P4501A (CYP1A) activity and fluorescent bile metabolites, as well as higher concentrations of naphthenic acids in bile. Cadmium, copper, nickel, and selenium were also elevated in white sucker liver tissue compared with the reference location. Based on the exposure profile and response pattern observed, effects on energy storage and utilization in white sucker from the Athabasca River most likely resulted from exposure to polycyclic aromatic hydrocarbons derived from petrogenic and pyrolytic sources. Environ Toxicol Chem 2017;36:2058-2067. © 2017 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".