Introductory gestures before songbird vocal displays are shaped by learning and biological predispositions
Bibliographic record
Abstract
ABSTRACT Introductory gestures are present at the beginning of many animal displays. For example, lizards start their head-bobbing displays with introductory push-ups and animal vocal displays begin with introductory notes. Songbirds also begin their vocal displays by repeating introductory notes (INs) before producing their learned song and these INs are thought to reflect motor preparation. Between individuals of a given species, the acoustic structure of INs and the number of times INs are repeated before song varies considerably. While similar variation in songs between individuals is known to be a result of learning, whether INs are also learned remains poorly understood. Here, using natural and experimental tutoring with male zebra finches, we show that mean IN number and IN acoustic structure are learned from a tutor, independent of song learning. We also reveal biological predispositions in IN production; birds artificially tutored with songs lacking INs still repeated a short-duration syllable, thrice on average, before their songs. Overall, these results show that INs, just like elements in song, are shaped both by learning and biological predispositions and suggest multiple, independent, learning processes underlying the acquisition of complex vocal displays.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".