Environmental concentrations of agricultural-use pesticide mixtures evoke primary and secondary stress responses in rainbow trout
Bibliographic record
Abstract
The present study sought to determine whether environmentally realistic mixtures of agriculturally important pesticides are stressful to fish. Juvenile rainbow trout were exposed for 96 h to concentrations of a pesticide mixture found in a waterway that is the focus of salmon restoration efforts (Nicomekl River, BC, Canada). This mixture contained organochlorine, organophosphorus, phenylurea, and triazine classes of pesticides. Fish given a realistic mixture exposure (total concentration, 1.01 µg/L) had increased plasma cortisol concentration, packed red cell volume, hematocrit (Hct), as well as decreased white cell volume, leukocrit (Lct). Similar changes in Hct and Lct were apparent after exposure to a lower concentration (0.186 µg/L). Interestingly, no changes in plasma cortisol concentration, Hct, or Lct were noted after exposure to a higher concentration (13.9 µg/L). This suggests that the exposure likely impaired the mechanisms enabling the stress response. Across all exposures, plasma glucose concentration was related to plasma cortisol concentration, not to pesticide mixture concentration. This suggests that a secondary stress response may be more related to variability in individual primary stress response than to differences in pesticide exposure concentrations. In summary, the present study indicates that salmon living in agrichemical-contaminated waterways may be experiencing stress, and this may pose a threat to their survival.
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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".