Tiger moths and the threat of bats: decision-making based on the activity of a single sensory neuron
Bibliographic record
Abstract
Echolocating bats and eared moths are a model system of predator-prey interaction within an almost exclusively auditory world. Through selective pressures from aerial-hawking bats, noctuoid moths have evolved simple ears that contain one to two auditory neurons and function to detect bat echolocation calls and initiate defensive flight behaviours. Among these moths, some chemically defended and mimetic tiger moths also produce ultrasonic clicks in response to bat echolocation calls; these defensive signals are effective warning signals and may interfere with bats' ability to process echoic information. Here, we demonstrate that the activity of a single auditory neuron (the A1 cell) provides sufficient information for the toxic dogbane tiger moth, Cycnia tenera, to decide when to initiate defensive sound production in the face of bats. Thus, despite previous suggestions to the contrary, these moths' only other auditory neuron, the less sensitive A2 cell, is not necessary for initiating sound production. However, we found a positive linear relationship between combined A1 and A2 activity and the number of clicks the dogbane tiger moth produces.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".