Identification of compounds in heavy fuel oil that are chronically toxic to rainbow trout embryos by effects-driven chemical fractionation
Bibliographic record
Abstract
The present study isolated and identified compounds in heavy fuel oil 7102 (HFO 7102) that are bioavailable and chronically toxic to rainbow trout embryos (Oncorhynchus mykiss). An effects-driven chemical fractionation combined the chemical separation of oil with toxicity testing and chemical analyses of each fraction to identify the major classes of compounds associated with embryo toxicity. Toxicity was assessed with 2 exposure methods, a high-energy chemical dispersion of oil in water, which included oil droplets in test solutions, and water accommodated fractions which were produced by oiled gravel desorption columns, and which did not contain visible oil droplets. Fractions of HFO with high concentrations of naphthalenes, alkanes, asphaltenes, and resins were nontoxic to embryos over the range of concentrations tested. In contrast, fractions enriched with 3- to 4-ringed alkyl polycyclic aromatic hydrocarbons (PAHs) were embryotoxic, consistent with published studies of crude oils and individual alkyl PAHs. The rank order of fraction toxicity did not vary between the exposure methods and was consistent with their PAH content; fractions with higher-molecular weight alkyl PAHs were the most toxic. Exposure of juvenile trout to most fractions of HFO induced higher activities of cytochrome P450 enzymes, with a rank order of potency that varied with exposure method and differed somewhat from that of embryotoxicity. Induction reflected the bioavailability of PAHs but did not accurately predict embryotoxicity.
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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) | 0.000 | 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".