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Record W4413407781 · doi:10.1016/j.anbehav.2025.123292

Assessing the cues required for mate choice copying in the plainfin midshipman fish

2025· article· en· W4413407781 on OpenAlexafffund
Ainsley Harrison-Weiss, A. F. Burgess, Madeleine G. Thomson, Aneesh P. H. Bose, Francis Juanes, Sigal Balshine

Bibliographic record

VenueAnimal Behaviour · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of VictoriaMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaLiber Ero FoundationGovernment of OntarioMcMaster University
KeywordsFish <Actinopterygii>CopyingMate choiceBiologyEcologyCaptivityZoologyCommunicationFisheryPsychologyMating

Abstract

fetched live from OpenAlex

When choosing a mate, females can rely on their own judgements of male quality or use social information from other females' choices. The use of social information to inform mating decisions is called mate choice copying. Theory predicts that mate choice copying should be strongest in species where females have few mates over the course of their life span because each mating constitutes a greater proportion of the female's expected reproductive value; however, most research on mate choice copying has thus far focused on species with highly promiscuous females. In this study, we use the plainfin midshipman, Porichthys notatus , a toadfish in which females typically choose one mate per year, to investigate whether females mate-choice copy and, if they do, which cues influence their decision making. We show that in the wild, plainfin midshipman females co-occur in nests more often than expected under random female choice. Additionally, we found that females in the laboratory did not base their mating decisions on the mere presence of another female or previously laid eggs; however, females were more likely to choose a male they had observed spawning with another female. Taken together, our results indicate that female plainfin midshipman do mate-choice copy, but only when they observe a spawning event. Understanding how different mating systems affect the strength of mate choice copying and which cues are necessary to elicit mate choice copying will help elucidate more broadly how this behaviour evolved and is 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)0.001
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 score0.055
Threshold uncertainty score0.431

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 studies0.0010.000
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 head0.034
GPT teacher head0.329
Teacher spread0.295 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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