Experience with predators shapes learning rules in larval amphibians
Bibliographic record
Abstract
Experience is essential for many prey species that must learn about predation risk to survive and reproduce. How prey incorporate information about predation risk via multiple learning events has been the subject of several studies, but results have been inconsistent, with cases where multiple conditionings have enhanced or weakened the learned responses. We hypothesized that such different outcomes reflect differences in the timing and frequency of past experience with the predator. To test this hypothesis, we provided naive wood frog tadpoles (Lithobates sylvaticus) with 4 days of experience with a predator. After a short (2 days) or longer (17 days) delay, tadpoles (naive or experienced) were conditioned to recognize the predator 0, 1, or 6 times. When tested the following day, all tadpoles from the short-delay group exhibited similar intensities of learned responses following 1 or 6 conditionings. However, a different pattern emerged when their background and recent experiences were separated by the longer time lag. Naive tadpoles responded similarly following the conditionings, but experienced tadpoles exhibited stronger responses after receiving multiple conditionings. We confirmed our hypothesis again using wild-caught tadpoles that had predator experience in their natural environment. Our results provide new insight into the surprisingly sophisticated learning rules for how certain aspects of past experience dictate the intensity of learned responses in tadpoles. These results also shed light on conflicting outcomes of past studies and have implications for conservation programs that make decisions about when and how often to train animals to recognize predators before their release.
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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 | 0.000 | 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) | 0.001 | 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 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".