Contribution of commonly analyzed polycyclic aromatic hydrocarbons (PAHs) to potential toxicity in early life stages of rainbow trout (<i>Oncorhynchus mykiss</i>)
Bibliographic record
Abstract
In a series of bio-effect-directed fractionation experiments, we investigated the potential toxicity of sediment extracts from a contaminated bay. A previous study investigated abnormalities and hepatic ethoxyresorufin O-deethylase (EROD) activities in rainbow trout (Oncorhynchus mykiss) larvae by exposing newly fertilized eggs to the total extract and to fractions separated by degree of aromaticity. A major part of the potential toxicity was isolated in a fraction containing polycyclic aromatic compounds (PACs). In this study, we prepared a synthetic PAC mixture with 17 commonly analyzed polycyclic aromatic hydrocarbons (PAHs) in amounts equimolar to those found in the sediment PAC fraction. The 17 PAHs, which included 11 of the 16 United States Environmental Protection Agency (US EPA) priority PAHs, were unable to account for the toxicopathic effects observed and could explain less than 4% of the total EROD induction. The lack of a clear relationship between toxicopathic effects and EROD induction underlines the need for a battery of biomarkers for estimating environmental risk. These results reveal the limits of our knowledge regarding compounds responsible for potential toxicity in field situations.
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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".