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Record W2981305883 · doi:10.1093/cz/zoz052

Contrasting female mate preferences for red coloration in a fish

2019· article· en· W2981305883 on OpenAlexafffund
Charel Reuland, Brett M. Culbert, Alessandro Devigili, Ariel F. Kahrl, John L. Fitzpatrick

Bibliographic record

VenueCurrent Zoology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Guelph
FundersVetenskapsrådetNatural Sciences and Engineering Research Council of CanadaWenner-Gren Foundation
KeywordsFish <Actinopterygii>Mate choiceZoologyBiologyFisheryEcologyMating

Abstract

fetched live from OpenAlex

Abstract Understanding how animals select their mates requires knowing the factors that shape mate preferences. Recent theoretical and empirical considerations suggest that female mating status can influence the degree to which a female engages in mate choice, with virgin females predicted to be less choosy than mated females. In this study, we investigated mate choice in both virgin and mated females in the pygmy halfbeak Dermogenys collettei. Halfbeaks are small, live-bearing, internally fertilizing freshwater fish that live in mixed-sex groups where females have ample opportunity to engage in mate choice. Using a dichotomous choice assay, we quantified and contrasted in virgin and mated females mate preferences for differences in male body size, beak size, and area of yellow and red coloration. We also examined how mating status influenced the amount of time a female associated with the first male encountered and the relative amount of time a female associated with each male. We demonstrate that mate preferences of female halfbeaks are driven primarily by the size of red coloration present on males. Females showed contrasting preferences based on mating status, with virgin females preferentially associating with drab males whereas mated females preferentially associate with males possessing large areas of red. Contrary to expectations, female mating status did not influence how females associate with the first males encountered or how females biased their association time among males. Although the precise drivers of these effects need further studying, our finding highlights a possible explanation for how variation in male ornamentation can be maintained.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.176

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 head0.062
GPT teacher head0.284
Teacher spread0.222 · 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

Citations10
Published2019
Admission routes2
Has abstractyes

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