Caterpillar sonic defences: diversity of vocalisations in silk and hawk moth (Bombycoidea) larvae
Bibliographic record
Abstract
Several Bombycoidea caterpillars, renowned for their large size and diverse appearances, possess an intriguing hidden talent – the ability to ‘vocalise’. Vocalisation is a rare form of sound production in insects, whereby sounds emanate from the oral cavity by air being forced through the foregut. Here, we report on vocalisation in 10 Bombycoidea species that occur across three families. Sounds in all 10 species are evoked in response to simulated predator attacks. Species were identified as vocalisers based primarily on video evidence of mouthparts being open during sound production. Vocalisations, when considered collectively across all 10 species studied, sound like a train of ‘hisses’ (sound units) that occur following an attack. Each sound unit comprises a series of pulses (4–104 on average) and is broadband with high dominant frequency (24–49 kHz on average). Given that vocalising species occur in different families across this large superfamily, we asked whether related species shared similar sound features. We found considerable overlap between sound characteristics of different vocalising species, suggesting a shared mechanism overall. However, distinct differences were also noted between families, suggesting that vocalisation may have evolved multiple times within Bombycoidea. The evolutionary origins and specific functions of vocalisation in caterpillars are discussed.
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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 | 0.001 | 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".