Oil exposure impairs predator–prey dynamics in larval red drum (Sciaenops ocellatus)
Bibliographic record
Abstract
The 2010 Deepwater Horizon (DWH) oil spill in the Gulf of Mexico was the largest spill in recent history and led to the exposure of many commercially and ecologically important fish species. Crude-oil exposure is known to result in compromised cardiorespiratory function and swim performance of fishes, presumably altering ecological performance by impairing the ability to capture prey or evade predators. However, this has yet to be empirically tested. This study assessed the impacts of oil exposure on thigmotaxis (avoidance of exposed areas), routine activity, and prey-capture ability in larval red drum (Sciaenops ocellatus) by using environmentally relevant concentrations of weathered-oil water-accommodated fractions (0–55.9 µg L–1 of total polycyclic aromatic hydrocarbons, ΣPAH). Oil exposure caused a dose-dependent increase in time spent in the exposed area of the arena, with an average three-fold increase at the highest dose, suggesting increased risk-taking. Although increased risk-taking resulted in 14% more area explored, oil-exposed individuals were significantly slower to catch prey and caught 67% less prey overall. Prey-capture ability did not appear to be related to cardiorespiratory or swimming impairments, because oil-exposed fish exhibited routine swim speeds and the distance travelled similar to those of the control, suggesting an alternate route of toxicity, such as cognitive impairments.
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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".