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Record W3091301058 · doi:10.1163/1568539x-bja10032

Courtship behaviour influences social partner choice in male guppies

2020· article· en· W3091301058 on OpenAlexafffund
Heather L. Auld, Jean‐Guy J. Godin

Bibliographic record

VenueBehaviour · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCourtshipEavesdroppingPoeciliaPsychologyPreferenceAttractivenessSocial psychologySexual attractionMate choiceCourtship displaySocial preferencesMatingDevelopmental psychologySexual behaviorZoologyBiologyFish <Actinopterygii>Computer security

Abstract

fetched live from OpenAlex

Abstract Although male courtship displays have evolved primarily to sexually attract females, they also generate inadvertent public information that potentially reveals the courter’s relative sexual attractiveness and the perceived quality and sexual receptivity of the female being courted to nearby eavesdropping male competitors, who in turn may use this information to bias their social partner choices. We tested this hypothesis by first presenting individual eavesdropping male guppies (Poecilia reticulata) the opportunity to simultaneously observe two demonstrator males whose courtship behaviour was manipulated experimentally to differ, following which we tested them for their preference to associate socially with either demonstrator males. Test males preferentially associated with the demonstrator male who they had previously observed courting a female over the other (non-courting) demonstrator. This social association preference was not expressed in the absence of a female to court. Our findings highlight the potential for sexual behaviour influencing male-male social associations in nature.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.072
GPT teacher head0.286
Teacher spread0.214 · 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

Citations1
Published2020
Admission routes2
Has abstractyes

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