Oil dispersion increases the apparent bioavailability and toxicity of diesel to rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
Diesel is a complex mixture containing polycyclic aromatic hydrocarbons, which persist after a spill, pass readily from water into tissues, and are toxic to early life stages of fish. The bioavailability and chronic toxicity of hydrocarbons dissolved into water from floating diesel (water-accommodated fraction) and chemically dispersed diesel (chemically enhanced water-accommodated fraction) were measured by the extent of ethoxyresorufin-O-deethylase (EROD) induction in juvenile rainbow trout (Oncorhynchus mykiss) and by the severity of blue sac disease in embryos. The water-accommodated fraction of floating diesel was virtually nontoxic to embryos at nominal concentrations up to 1,000 mg/L, causing only small weight changes. Liver EROD induction in juvenile trout was only observed at the highest nominal water-accommodated fraction concentration (10,000 mg/L). Chemical dispersion increased the bioavailability and toxicity of diesel to trout by 100-fold. Diesel chemically enhanced water-accommodated fraction induced EROD activity, caused blue sac disease, and impaired development and growth of embryonic trout at nominal concentrations as low as 10 mg/L; 88% mortality occurred at 100 mg/L. However, when total hydrocarbon concentrations were measured, differences between dispersed and undispersed diesel disappeared, with a median lethal concentration of 8 mg/L of total hydrocarbons and sublethal median effective concentrations ranging from 1.3 to 6.1 mg/L. Dispersion of diesel by high-energy mechanical mixing was recently reported to cause acute lethality to juvenile trout between 40 and 200 mg/L. Therefore, dispersion of oil by any means increases the bioavailability and apparent toxicity of diesel to fish embryos without changing the toxicity of its components. Nevertheless, in an actual spill, dispersion of diesel increases the effects of oil on fish populations.
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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".