Temperature matters: Acute and latent toxicity of diluted bitumen to developing salmon is potentiated by a modest increase in water temperature
Bibliographic record
Abstract
Heavy crude oil, like bitumen, is used globally for plastics, petrochemicals and road surfacing. Canada's oil sands are the world's third largest crude oil reserve, and diluted bitumen (dilbit) is transported across North America primarily via pipeline and rail. Two environmentally-relevant concentrations of dilbit were used with a suite of toxicological endpoints to determine if a 3 °C increase in ambient temperature ( T a ) water modulated the effects of dilbit to coho salmon ( Oncorhynchus kisutch ) when exposed from fertilization to swim-up. The 10–20 % increase in mortality and 25 % reduction in hypoxia tolerance with dilbit exposure was magnified by 18 % and 40 %, respectively, in warmer water. Consequences of dilbit exposure persisted after 6 weeks of additional rearing in clean T a water but were greatest in fish exposed to dilbit at elevated temperature: additional 20 % mortality and 30 % decrease in mass relative to controls, and a residual 20 % reduction in hypoxia tolerance not seen with dilbit exposure alone. Relatively lower induction of the Phase I biotransformation enzyme cyp1a and greater tissue PAC content in warm-exposed coho suggests reduced PAC metabolism as a mechanism for the observed potentiation. Thus, seasonal fluctuations and baseline increases in water temperature from climate change can exacerbate the adverse effects of oil spills on developing fish.
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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 | 0.000 | 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) | 0.003 | 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".