Predation risk shapes the use of conflicting personal risk and social safety information in guppies
Bibliographic record
Abstract
When faced with uncertainty, animals can benefit from using multiple sources of information in order to make an optimal decision. However, information sources (e.g., social and personal cues) may conflict, while also varying in acquisition cost and reliability. Here, we assessed behavioral decisions of Trinidadian guppies (Poecilia reticulata), in situ, when presented with conflicting social and personal information about predation risk. We positioned foraging arenas within high- and low-predation streams, where guppies were exposed to a personal cue in the form of conspecific alarm cues (a known indicator of risk), a novel cue, or a control. At the same time, a conspecific shoal (a social safety cue) was either present or absent. When social safety was absent, guppies in both populations showed typical avoidance responses towards alarm cues, and high-predation guppies showed their typical avoidance of novel cues (i.e., neophobia). However, the presence of social safety cues was persuasive, overriding the neophobia of high-predation guppies and emboldening low-predation guppies to ignore alarm cues. Our experiment is one of the first to empirically assess the use of safety and risk cues in prey, and suggests a threshold level of ambient risk which dictates the use of conflicting social and personal information.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".