Toxicity of Weathered Sediment-Bound Dilbit to Early Life Stages of Zebrafish (<i>Danio rerio</i>)
Bibliographic record
Abstract
Due to high viscosity, bitumen extracted from the Alberta oil sands is diluted with natural gas condensates to form diluted bitumen (dilbit) to facilitate transport through pipelines. Dilbit that is spilled into or near a waterbody is subject to environmental weathering processes such as evaporation and interaction with sediments. This is the first study that assessed the toxicity of weathered sediment-bound dilbit (WSD) to fish early life stages. Exposure of zebrafish ( Danio rerio ) embryos to water-soluble fractions (WSFs) or water-accommodated fractions (WAFs) of WSD from 30 min to 120 h postfertilization resulted in pericardial edema, yolk sac edema, and incidences of uninflated swim bladder. The presence of oil-mineral aggregates (OMAs) in the WAFs greatly increased toxicity, despite all fractions having similar concentrations of dissolved polycyclic aromatic hydrocarbons (PAHs). There were greater cyp1a mRNA abundances in larvae exposed to WAFs, suggesting that there were differences in bioavailability of PAHs between fractions. However, there was little evidence that embryotoxicity was caused by oxidative stress. Results suggest that evaporation and sediment interaction do not completely attenuate toxicity of dilbit to zebrafish early life stages, and OMAs in exposures exacerbate toxicity.
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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) | 0.001 | 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".