Effects of Diesel on Survival, Growth, and Gene Expression in Rainbow Trout (<i>Oncorhynchus mykiss</i>) Fry
Bibliographic record
Abstract
Diesel spills are all too frequent disturbances of freshwater ecosystems, largely as a result of the quantities transported and consumed. Assessing the risk that such events may pose to aquatic life remains a difficult process, because of the complexity of this hydrocarbon mixture and our limited knowledge of its toxicity. A diesel spike experiment with rainbow trout (Oncorhynchus mykiss) fry was carried out to fill this knowledge gap. Survival, growth, and gene expression changes were assessed and toxicity thresholds were determined. Whereas the biological end points were consistent in the determination of (sub)lethal doses, microarrays supplied additional information on the mechanism of toxicity (oxygen deprivation) and potential long-term effects (feminization, immune system alterations) of diesel exposure on salmonids. Hemoglobins, prostaglandins, cytochromes, and gluthathion-S-transferases were among the molecular biomarkers proposed for use in future risk assessments based on microarray results. By bridging traditional toxicity testing with recent microarray technologies, this study shows the potential of genomics tools in ecotoxicity studies as well as industrial applications, including risk assessment, in the near future.
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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".