How do Caterpillars Detect Vibration? Proleg Sensory Hairs as Vibration Receptors in Drepana Arcuata (Drepanidae) and Trichoplusia ni (Noctuidae)
Bibliographic record
Abstract
It is known that substrate-borne vibrations are detected by insects from multiple taxa and life stages, including adults and larvae.Therefore, in this thesis I aimed to answer the question "How do caterpillars detect vibration?".For this purpose, I made neurophysiological experiments on proleg hairs of Drepana arcuata and Trichoplusia ni caterpillars.In these experiments, two types of mechanical stimuli were applied to the proleg hair: 1) sine vibrational signals with varying frequencies and 2) single push/pull stimuli.Amplitudes of stimuli ranged from sub-to supra-threshold and stimuli were applied in multiple directions to test for sensory directionality.With this, I showed that the sensory activity of the hair can be characterized as a rapid adapting response, that it has directional sensitivity and presents some phase-locking.In conclusion, the sensory hairs here evaluated can respond to vibration, which leaves them as potential candidates for substrate-borne vibration receptors in these caterpillars.iii
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".