MétaCan
Menu
Back to cohort
Record W4417006351 · doi:10.1098/rsbl.2025.0526

Dance complexity is not associated with cognitive performance but positively linked with body condition and attractiveness in male zebra finches

2025· article· en· W4417006351 on OpenAlexafffund
Marie Barou‐Dagues, Frédérique Dubois

Bibliographic record

VenueBiology Letters · 2025
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDanceAttractivenessCognitionEffects of sleep deprivation on cognitive performancePreferenceZebra finchContemporary dance

Abstract

fetched live from OpenAlex

Female preference for males with enhanced cognitive abilities has been reported in many species, but it remains unclear which sexual signals reflect such skills. We hypothesized that male dance performance is correlated with cognitive performance, body condition and increased attractiveness in zebra finches (Taeniopygia castanotis). We collected dance behaviours from 164 male displays and assessed male condition, attractiveness and performance in four cognitive tasks: associative learning, motor learning, spatial learning and inhibitory control. Variance in male displays was mainly explained by two independent features: dance duration and dance complexity. Dance duration was not correlated with male cognitive performance, body condition or attractiveness, while dance complexity was significantly linked with body condition and attractiveness and marginally linked with motor learning performance. While our findings suggest that male dance attributes are unlikely to serve as indicators of general cognition in zebra finches, dance complexity might reflect general health and may be used by females as a mate-choice criterion. Despite the need for replication, our findings do not support the idea that intersexual selection based on male dance displays shapes the evolution of general cognition.

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 score0.024
Threshold uncertainty score0.691

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 studies0.0000.001
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 head0.037
GPT teacher head0.316
Teacher spread0.279 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueBiology LettersSame topicPrimate Behavior and EcologyFrench-language works237,207