Effects of pre‐winter cortisol exposure on condition, diet, and morphology of wild juvenile brown trout (<i>Salmo trutta</i>)
Bibliographic record
Abstract
Winter is an energetically challenging period for many animals in temperate regions because of the relatively harsh environmental conditions and reduction in food availability during this season. Moreover, stressors experienced by individuals in the fall can affect their subsequent foraging strategy and energy stores after exposure has ended, referred to as carryover effects. We used exogenous cortisol manipulation of wild juvenile brown trout (Salmo trutta) in the fall to simulate a physiological stress response and then investigated short-term (2 weeks) and long-term (4 months) effects on condition metrics (hepatosomatic index and water muscle content), diet (stomach contents and stable isotopes), and morphology during growth in freshwater. We revealed some short-term impacts, likely due to handling stress, and long-term (seasonal) changes in diet, likely reflecting prey availability. Unfortunately, we had very few recaptures of cortisol-treated fish at long-term sampling, limiting detailed analysis about cortisol effects at that time point. Nonetheless, the fish that were sampled showed elevated stable isotopes, suggestive of a cortisol effect long after exposure. This is one of few studies to investigate whether cortisol influences foraging and morphology during juvenile growth, thus extending the knowledge of proximate mechanisms influencing ecologically-relevant phenotypes.
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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 | 0.001 |
| 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".