Vibration‐mediated territoriality in the warty birch caterpillar <i>Drepana bilineata</i>
Bibliographic record
Abstract
Abstract The warty birch caterpillar Drepana bilineata produces two distinct types of vibrational signals (mandible drumming and anal scraping) during interactions with conspecifics. Vibrational signalling is characterized using standard and high‐speed videography synchronized with laser‐doppler vibrometry, and behavioural experiments test the hypothesis that signalling functions to advertise occupancy of birch ( Betula ) leaves. Drumming involves raising the head and striking the leaf with the sharp edges of the open mandibles. Anal scraping involves dragging a pair of specialized oar‐shaped setae against the leaf surface. Staged encounters between leaf residents and conspecific intruders result in the resident signalling, with rates increasing as the intruder moves closer. Intruders signal significantly less often than residents. Conflicts are typically resolved within a few minutes, with the resident winning in 61% of the trials, and the intruder winning in 6%. Contests that last more than 30 min are deemed ‘ties’ and comprise the remaining 33% of trials. The results support the hypothesis that vibrational signals function to advertise leaf occupancy. Vibrational communication is believed to be widespread in Drepanoidea caterpillars, but has only been described in two species to date: D. bilineata (present study) and Drepana arcuata . It is proposed that differences in territorial behaviour and signalling between these species are related to their relative investments in silk leaf mats and shelters. The proximate and ultimate bases for the evolution of vibrational communication 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 | 0.000 | 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".