Song bout length is indicative of spatial learning in European starlings
Bibliographic record
Abstract
Female songbirds are attracted to male song, and song may honestly signal male quality. Song is a phenotypic expression of a complex learned behavior and therefore could be indicative of other cognitive abilities. Stressful conditions during early development are known to adversely affect the development of the mammalian and avian brain, and recent evidence suggests a positive association between song quality and learning ability. However, prior studies have not assessed how early-life stress affects both general cognitive functioning and song learning. We subjected nestling- and juvenile-caught European starlings (Sturnus vulgaris) to either an ad libitum or food-restricted diet until approximately 90 days of age. As adults, birds’ cognitive abilities were assessed via spatial foraging and social learning tasks, while controlling for the effects of neophobia. Song learning was assessed in undirected and directed singing contexts. We found that birds fed the ad libitum diet had significantly longer song bouts in both singing contexts, made fewer errors in the spatial foraging task, but performed worse on the social learning task than food-restricted birds. Overall, song performance only correlated with performance on the spatial foraging task: Males with longer mean song bouts in the directed singing context committed fewer errors. These data suggest that the neural structures supporting song and spatial abilities are both affected by nutritional stress during development. Female starlings are attracted to longer song bouts and may thus use song bout length to infer spatial learning abilities of potential mates.
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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) | 0.001 | 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".