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Record W2113008098 · doi:10.1093/beheco/aru137

Telemetric and video assessment of female response to male vocal performance in a lek-mating manakin

2014· article· en· W2113008098 on OpenAlexaff
Dugan F. Maynard, Kara‐Anne A. Ward, Stéphanie M. Doucet, Daniel J. Mennill

Bibliographic record

VenueBehavioral Ecology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsLek matingBiologyMate choiceMatingTelemetryAttractionAdult maleSexual selectionZoologyEcology

Abstract

fetched live from OpenAlex

Sexual signals play an important role in mate attraction. In this study, we explore male vocal behavior and female mate attraction in long-tailed manakins, tropical lekking birds where males perform cooperative displays to attract females, and males provide only gametes to choosy females. We monitored female visitation at 37 sites using two techniques: video recordings and automated radiotelemetry. Simultaneously, we used digital recorders to sample male vocal behavior, quantifying vocal output as well as frequency matching and temporal synchrony in male–male duets. We compared male vocal performance to the rate at which females visited male display sites. Video data revealed that both male vocal output and the temporal synchrony of male–male duets were positively related to female visitation, matching our expectations. Telemetry data, in contrast, revealed no such relationship. Our results suggest that telemetry data may yield biased estimates of patterns of female choice, because the tracked females may not adequately represent the pool of potential female visitors to leks. We also demonstrate that male vocal behavior and female visitation vary, in concert, with time of day, peaking in the early morning, with a pronounced drop in the mid-day heat. We compare these results with those of another study, of the same species, in a montane environment with cooler daytime temperatures.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.350
Teacher spread0.320 · 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

Citations12
Published2014
Admission routes1
Has abstractyes

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