Linking predator risk and uncertainty to adaptive forgetting: a theoretical framework and empirical test using tadpoles
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
Hundreds of studies have examined how prey animals assess their risk of predation. These studies work from the basic tennet that prey need to continually balance the conflicting demands of predator avoidance with activities such as foraging and reproduction. The information that animals gain regarding local predation risk is most often learned. Yet, the concept of 'memory' in the context of predation remains virtually unexplored. Here, our goal was (i) to determine if the memory window associated with predator recognition is fixed or flexible and, if it is flexible, (ii) to identify which factors affect the length of this window and in which ways. We performed an experiment on larval wood frogs, Rana sylvatica, to test whether the risk posed by, and the uncertainty associated with, the predator would affect the length of the tadpoles' memory window. We found that as the risk associated with the predator increases, tadpoles retained predator-related information for longer. Moreover, if the uncertainty about predator-related information increases, then prey use this information for a shorter period. We also present a theoretical framework aiming at highlighting both intrinsic and extrinsic factors that could affect the memory window of information use by prey individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| 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