Ecological uncertainty and antipredator behaviour: an integrative perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to its unforgiving nature, predation pressure exerts strong selection pressure on the behaviour of prey animals. As a result, prey are forced to balance the conflicting demands of successfully detecting and avoiding predators and the need to engage in other fitness-related activities such as foraging, mating and social behaviour. Here, we provide an overview of the role that individual predator avoidance decisions plays in constraining behavioural phenotypes and how past experience with risks shapes current (and future) trade-offs, physiological and life history investments. Critically, access to reliable risk assessment information allows prey to respond to spatially and temporally variable predation risks. Uncertainty of predation risks is expected to limit the ability of prey to make short- and longer-term adjustments responses to predation threats, potentially increasing the indirect costs of predation. We describe a ‘landscape of information’ in which prey rely on publicly available risk assessment information to reduce the uncertainty of predation risks associated with variable threats and the potential impact of natural and anthropogenic environmental factors which may limit information availability. Despite a long tradition of research into the antipredator trade-offs made by prey animals, there remain a number of important unanswered questions.
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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 | 0.000 | 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) | 0.000 | 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 it