Background level of risk determines how prey categorize predators and non-predators
Bibliographic record
Abstract
Much of the plasticity that prey exhibit in response to predators is linked to the prey's immediate background level of risk. However, we know almost nothing of how background risk influences how prey learn to categorize predators and non-predators. Learning non-predators probably represents one of the most underappreciated aspects of anti-predator decision-making. Here, we provide larval damselfish (Pomacentrus chrysurus) with a high or low background risk and then try to teach them to recognize a cue as non-threatening through the process of latent inhibition. Prey from the low-risk background that were pre-exposed to the novel odour cues in the absence of negative reinforcement for 3 days, and then provided the opportunity to learn to recognize the odour as threatening, failed to subsequently respond to the odour as a threat. Fish from the high-risk background showed a much different response. These fish did not learn the odour as non-threatening, probably because the cost of falsely learning an odour as non-threatening is higher when the background level of risk is higher. Our work highlights that background level of risk appears to drive plasticity in cognition of prey animals learning to discriminate threats in their environment.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".