Using the reactive scope model to redefine the concept of social stress in fishes
Bibliographic record
Abstract
The term 'social stress' has traditionally referred to physiological stress responses induced by the behaviour of conspecifics, particularly aggression or agonistic behaviours. Here, we review the physiological consequences of social status in fishes using the reactive scope model (RSM) to explain the divergent physiological phenotypes of dominant and subordinate fish. The RSM plots levels of different physiological mediators (e.g. behaviour, glucocorticoid hormones) over time, using them to define functional ranges that differ in their consequences for the animal. We discuss differences in growth, reproduction and tolerance of environmental challenges, all of which are suppressed in subordinate individuals, and focus on the underlying mechanisms that give rise to these phenotypes. Repeated and/or continual activation of the hypothalamic-pituitary-interrenal (HPI) axis in subordinate fish can lead to prolonged elevation of cortisol, a key physiological mediator. In turn, this increases physiological 'wear and tear' in these individuals, lowering their reactive scope (i.e. the physiological range of a healthy animal) and increasing their susceptibility to homeostatic overload. That is, they experience social stress and, ultimately, their capacity to cope with environmental challenges is limited. By contrast, reactive scope is maintained in dominant individuals, and hence they are better able to tolerate environmental challenges. Redefining social stress in terms of the RSM allows us to overcome the ambiguities and limitations associated with the concept of stress.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".