Current predation risk has opposing effects on social learning of foraging locations across two guppy populations
Bibliographic record
Abstract
Social learning, where animals learn from other individuals, occurs in many diverse species. The influential but debated 'costly information' hypothesis posits that animals will rely more on social information in high-risk contexts, such as under increased predation risk. We examined and compared the effects of perceived predation risk on social learning of foraging sites in female Trinidadian guppies from wild and domestic populations raised in common-garden environments. We used a demonstrator-observer pairing where a subject could observe conspecific 'demonstrators' feeding from one of two feeders, and measured whether the observer subsequently spent more time at a demonstrated or non-demonstrated feeder. We manipulated perceived predation risk using alarm cue (conspecific skin extract). Stress responses and social learning differed between the two populations. Most notably, high predation risk enhanced social learning in the wild-type guppies, but depressed it in the domestic guppies. Thus, fish from both populations were able to socially learn, but under opposing contexts. These results suggest social learning propensities are the product of multiple interacting systems, and biases to favour social learning can emerge dependent on evolutionary history and current conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".