Slime moulds use heuristics based on within-patch experience to decide when to leave
Why this work is in the frame
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Bibliographic record
Abstract
Animals foraging in patchy, non-renewing or slowly renewing environments must make decisions about how long to remain within a patch. Organisms can use heuristics ('rules of thumb') based on available information to decide when to leave the patch. Here, we investigated proximate patch-departure heuristics in two species of giant, brainless amoeba: the slime moulds Didymium bahiense and Physarum polycephalum. We explicitly tested the importance of information obtained through experience by eliminating chemosensory cues of patch quality. In P. polycephalum, patch departure was influenced by the consumption of high, and to a much lesser extent low, quality food items such that engulfing a food item increased patch-residency time. Physarum polycephalum also tended to forage for longer in darkened, 'safe' patches. In D. bahiense, engulfment of any food item increased patch residency irrespective of that food item's quality. Exposure to light had no effect on the patch-residency time of D. bahiense. Given that these organisms lack a brain, our results illustrate how the use of simple heuristics can give the impression that individuals make sophisticated foraging decisions.
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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