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Record W2090550199 · doi:10.1098/rspb.2007.0432

Courtship and genetic quality: asymmetric males show their best side

2007· article· en· W2090550199 on OpenAlexafffund
Mart R. Gross, Ho Young Suk, Cory T Robertson

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2007
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsWestern UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCourtshipQuality (philosophy)Evolutionary biologyBiologyCourtship displayCommunicationPsychologyZoologyPhysics

Abstract

fetched live from OpenAlex

Fluctuating asymmetry (FA), the small random deviations from perfect morphological symmetry that result during development, is ubiquitous throughout the animal kingdom. In many species, FA seems to play a role in mate choice, perhaps because it signals an individual's genetic quality and health. However, the relationship between an individual's FA and behaviour is generally unknown: what do more asymmetric individuals do about their own asymmetry? We now show for the first time that individuals respond behaviourally to their own morphological FA in what appears to be an adaptive manner. During courtship, male guppies exhibiting high FA in ornamental colour, bias their displays towards their more colourful body side, thus potentially increasing their attractiveness by exaggerating the quantity of their orange signal. This appears to be a strictly behavioural male response to cues provided by females, as it does not occur when males court a non-reactive model female. Whether inferior males realize any mating advantage remains uncertain, but our study clearly demonstrates a behavioural response to random morphological asymmetries that appears to be adaptive. We propose that the tendency to show or otherwise use a 'best side' is common in nature, with implications for sexual signalling and the evolution of more pronounced asymmetries.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.101
GPT teacher head0.358
Teacher spread0.258 · 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.

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

Citations33
Published2007
Admission routes2
Has abstractyes

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