MétaCan
Menu
Back to cohort
Record W2288517800 · doi:10.1080/09524622.2016.1138883

Stridulation of the clear-wing meadow katydid<i>Xiphelimum amplipennis</i>, adaptive bandwidth

2016· article· en· W2288517800 on OpenAlexafffund
Glenn K. Morris, Holger Braun, Christian S. Wirkner

Bibliographic record

VenueBioacoustics · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAcousticsWingSound (geography)StridulationBioacousticsSound intensityGeologyPhysicsSound production

Abstract

fetched live from OpenAlex

Rubbed wings, analysed calls and a peculiar sound generator structure in males of a conocephaline katydid, Xiphelimum amplipennis, give insight into the making of broadband spectra. High shear forces are indicated by a robust forewing morphology. Intensity is high for frequencies in a 20–60 kHz ultrasonic band. Besides a typical katydid sound-radiating mirror and harp, this insect has a long costal series of semi-transparent specular sound radiators. These wing cells are loaded behind by an enlarged and partitioned subwing air space. Calls repeat steadily with five different time domain sound elements. Distinctive spectra are associated with two of these, giving stepwise frequency modulation that combines to create the exceptionally wide spectral breadth. Broadcast sound levels at 10 cm dorsal, right and left, are near 100 dB. Costal wing-cell sound radiation was explored by loading the costal “speculae” with wax. This produced almost no decrease in lateral sound levels, but did alter spectral content. Apparently, this insect’s costal region both baffles and radiates. The species lives at high densities in cluttered vegetation and sound signal attenuation should code via spectral shape for distance ranging.

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)0.000
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.249
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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBioacousticsSame topicAnimal Vocal Communication and BehaviorFrench-language works237,207