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Record W2027100314 · doi:10.1139/z01-212

Acoustic communication in the Palaearctic red cicada,<i>Tibicina haematodes</i>: chorus organisation, calling-song structure, and signal recognition

2002· article· en· W2027100314 on OpenAlexvenueno aff
J. Sueur, Thierry Aubin

Bibliographic record

VenueCanadian Journal of Zoology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsChorusBiologyDuration (music)SIGNAL (programming language)Sexual selectionAnimal communicationCommunicationAcousticsSpeech recognitionPsychologyZoologyComputer scienceLiteraturePhysics

Abstract

fetched live from OpenAlex

Males of the Palaearctic red cicada, Tibicina haematodes, produce calling songs that are attractive to both sexes. For the first time we (i) describe the organisation of the chorus formed by aggregating males, (ii) analysed the physical characteristics of the calling song, and (iii) used playback experiments of natural, modified, and allospecific signals to investigate the signal-recognition process. Males overlap each other's calling song and try to call first and last during a chorus, leading to what we term domino and last-word effects, respectively. The calling song consists of a two-part sequence made up of a succession of pulses. It is characterized by slow and fast amplitude modulations and three frequency bands. The structure of the signal varied among individuals in both temporal and frequency parameters. Our playback experiments showed that males make a rough analysis of frequency and duration features of the signal. They pay no attention to amplitude modulations. Because males are not capable of precise analysis, they reply to various allospecific calling songs. Females' analysis of the calling song being difficult to test, the role of this signal in sexual selection still needs to be documented.

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 score0.493
Threshold uncertainty score0.991

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 head0.031
GPT teacher head0.242
Teacher spread0.212 · 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

Citations39
Published2002
Admission routes1
Has abstractyes

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