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Record W2606082980 · doi:10.1093/biolinnean/blw029

Hearing sensitivity is more relevant to acoustic conspicuousness than to mechanical constraints in crambid moths

2017· article· en· W2606082980 on OpenAlexafffund
Ryo Nakano, Andrew C. Mason

Bibliographic record

VenueBiological Journal of the Linnean Society · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersUniversity of Toronto Scarborough
KeywordsHuman echolocationBiologySympatric speciationPredationPopulationIntraspecific competitionZoologyEcologyNeuroscience

Abstract

fetched live from OpenAlex

Moths evolved tympanal hearing organs to detect the echolocation calls of predatory bats. Moths’ auditory responses have been examined mainly for their sensitivity to the frequencies of bat cries: tympanate moths are basically tuned to the call frequencies of sympatric bats. Here, we add the finding that hearing sensitivity to ‘pulse duration’ in crambid moths is also affected by predation pressure from echolocating bats. Analysis of interspecific variation showed that minimum auditory thresholds had a significantly negative relationship with the forewing surface area, that is, acoustic conspicuousness to bat sonar, but no relationship with head width, which was assumed to correlate with tympanal organ size. Auditory thresholds increased as pulses shortened in the 1–10 ms duration range, and conspicuous moths with larger wing areas had lower thresholds than smaller moths. By contrast, ‘intraspecific’ variation, within a single population of the lurcerne moth, revealed no relationship between forewing area and any auditory characteristics. Moth hearing adapts to the echolocation pulse duration of sympatric bat communities, suggesting that evolutionary modification of hearing sensitivity is related to acoustic conspicuousness based on moth wing area.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.055
GPT teacher head0.281
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes2
Has abstractyes

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