High background risk induces risk allocation rather than generalized neophobia in the fathead minnow
Bibliographic record
Abstract
Abstract To cope with the heterogeneous nature of predation and the trade-off between predator avoidance and foraging, prey animals have evolved several cognitive rules. One of these is the risk allocation hypothesis, which predicts that in environments with long periods of sustained high risk, individuals should decrease their antipredator effort to satisfy their metabolic requirements. The neophobia hypothesis, in turn, predicts increased avoidance of novel cues in high-risk habitats. Despite the recent interest in predator-induced neophobia across different sensory channels, tests of such generalized neophobia are restricted to a single fish taxon, the Cichlidae. Hence, we retested the generalized neophobia hypothesis in fathead minnows Pimephales promelas, a small schooling North American cyprinid fish. From hatching onward, minnows were exposed to conspecific alarm cues, which indicate predation risk, or distilled water in a split-clutch design. After 1 month, shoaling behavior was examined prior and subsequent to a mechanical predator disturbance. Fish previously exposed to elevated background risk formed compact shoals for a shorter time interval after the stimulus compared with controls. These results contrast previous studies of generalized neophobia but match the risk allocation hypothesis. Consequently, risk allocation and generalized neophobia are not ubiquitous cognitive rules but instead evolved adaptations of different taxa to their respective environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".