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Record W1636550711

Andean ultrasonics: Bioacoustics of two tropical montane katydids

2009· article· en· W1636550711 on OpenAlexafffundvenue
Glenn K. Morris

Bibliographic record

VenueCanadian acoustics · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBioacousticsMontane ecologyBiologyAcousticsPulse (music)MatingEcologyEngineeringPhysicsTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Ultrasonics are waves of airborne sound longer than ~1.7 cm (20 kHz) that, by definition, cannot be heard.The term distinguishes sound frequencies above the upper limit of human frequency sensitivity.But of course a dog, a bat or a cricket may hear such waves: animal sensory systems have 'unhuman' capacities.Ultrasonic is only a convenient descriptor for 'wavelengths above the limit of detection', applied illogically to animal species that hear these waves 'just fine'.Some species of the singing insects known as 'katydids' (Tettigoniidae) produce and hear ultrasonics.The males make their sounds perching on plants.They rub their forewings together, which excites the oscillation of forewing membranes as sound radiators.Male calls travel through grasses, shrubs or forests to be heard by distant females: these females localize the singer and approach him for mating.Why such carriers should be ultrasonic is puzzling, because ultrasonic wavelengths interact poorly with plant environments; they don't carry well, and being higher energy at a given sound level, are relatively more costly to produce than audio frequencies.Ultrasonics would not seem a good choice for a beacon directed to potential mates at long range.Two such katydid species comprise the genus Myopophyllum, both with a very high ultrasonic carrier.This is about the physical structure of their sounds and how they have evolved to make them 'elastically'.At present the 'why' of their ultrasonics remains a puzzle.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.204
Teacher spread0.180 · 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 teacher head, 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

Citations0
Published2009
Admission routes3
Has abstractyes

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