Behavioural responses to video and live presentations of females reveal a dissociation between performance and motivational aspects of birdsong
Bibliographic record
Abstract
Understanding the regulation of social behavioural expression requires insight into motivational and performance aspects of social behaviours. While a number of studies have independently investigated motivational or performance aspects of social behaviours, few have examined how these aspects relate to each other. By comparing behavioural variation in response to live or video presentations of conspecific females, we analysed how variation in the motivation to produce courtship song covaries with variation in performance aspects of courtship song in male zebra finches (Taeniopygia guttata). Consistent with previous reports, we observed that male zebra finches were less motivated to produce courtship songs to videos of females than to live presentations of females. However, we found that acoustic features that reflect song performance were not significantly between songs produced to videos of females and songs produced to live presentations of females. For example, songs directed at video presentations of females were just as fast and stereotyped as songs directed at live females. These experimental manipulations and correlational analyses reveal a dissociation between motivational and performance aspects of birdsong and suggest a refinement of neural models of song production and control. In addition, they support the efficacy of videos to study both motivational and performance aspects of social behaviours.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".