Short-term stress: effects on cortisol levels and carotenoid spots in Arctic char (<i>Salvelinus alpinus</i>)
Bibliographic record
Abstract
Earlier studies have shown that the carotenoid pigmentation in Arctic char (Salvelinus alpinus (L., 1758)) is connected to stress responsiveness. These studies also suggested that the pigmentation is dynamic and can change quickly. Therefore, we wanted to investigate the effect of a short-term stressor on the number of carotenoid spots before and after certain time intervals after the stressor. Individuals were exposed to a net-restraint stressor for 1 min and then assigned a recovery time of either 0, 1, 2, 8, or 24 h. Photographs were taken before the stressor and after the recovery time to count carotenoid spots and to look at the relative changes over time. Behaviour during the stressor and cortisol levels after the assigned recovery time were evaluated. We found that the change in spottiness, measured as the ratio of spots after and before the stressor, changed with recovery time on the right side but not on the left side. Furthermore, left-side spots were correlated with struggling activity. Thus, carotenoid pigmentation seems to be lateralized, with more static spots on the left side connected to stress responsiveness, whereas spots on the right side seem to be more dynamic.
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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".