Selection for evasive mimicry imposed by an arthropod predator
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
It has long been hypothesized that a species that is relatively easy to catch by predators may face selection to resemble a species that is harder to catch. Several experiments using avian predators have since supported this “evasive mimicry” hypothesis. However, the sudden movement of artificial evasive prey in each of the above experiments may have startled the predators, generating an avoidance response unrelated to difficulty of capture. Additionally, in the above experiments, the catchability of prey was all or nothing, while in nature predators may occasionally catch evasive prey or fail to catch slower species, which might inhibit learning. Here, using mantids as predators, we conducted an experimental test of the evasive mimicry hypothesis that circumvents these limitations, using live painted calyptrate flies with modified evasive capabilities as prey. We found that mantids readily learned to avoid pursuing the more evasive prey types. Warning signals based on evasiveness and their associated mimicry may be widespread phenomena in nature. These findings not only further support its plausibility but demonstrate that even arthropod predators can select for it.
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 | 0.000 | 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) | 0.002 | 0.002 |
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