Dance complexity is not associated with cognitive performance but positively linked with body condition and attractiveness in male zebra finches
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".