SONGS AND CALLS: PERSPECTIVES ON CREATING A GLOBAL DEFINITION
Bibliographic record
Abstract
Bird vocalizations have been split historically into two main categories: calls and songs. This categorization has been based mainly on the duration and complexity of the vocalization, although other criteria including function, development, and phylogeny have been included to separate both vocalizations. The increasing number of studies over the last decade examining the structure, function, and evolution of vocalizations, especially for species that breed in the tropics, have revealed that the current definitions for songs and calls no longer match our current knowledge of bird vocalizations. Here, we propose a new global definition for calls and songs that matches our current knowledge on this topic. Additionally, we review several key assumptions that have been used to classify songs, and by association calls, and we present clear examples that contradict these previous assumptions, and thereby limit the definition of songs and calls. Our proposed call and song definitions correct for the ambiguity of previous definitions that use complexity and duration, or omit vocalization functions, and reflects the diverse and multifunctional properties of avian vocalizations.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.012 | 0.029 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".