Vocal repertoire of cooperatively breeding Smooth-billed Anis
Bibliographic record
Abstract
Calls are functionally diverse signals that mediate behavior in a wide variety of contexts in both passerines and non-passerines. However, the call-based acoustic communication systems of non-passerines have received less attention from investigators than those of passerines. We examined the vocal repertoire of Smooth-billed Anis (Crotophaga ani), cooperatively breeding cuckoos that live in groups with multiple breeding pairs. We recorded calls from 22 groups over two breeding seasons at the Cabo Rojo National Wildlife Refuge in Puerto Rico. We identified 11 call types and one group vocalization, and used an automated sound measurement program to quantify their acoustic features. Discriminant function analysis (DFA) correctly classified 74.2% of calls based on these features. The vocal repertoire of Smooth-billed Anis is larger than that reported for the three other species in the subfamily Crotophaginae. Smooth-billed Anis have at least two alarm calls, two nest-specific calls, and one nest defense call. We also identified one possible signal of aggressive intent, one possible appeasement signal, and two calls that may communicate identity. The relatively large vocal repertoire of Smooth-billed Anis and association of distinct call types with different functions and contexts supports the main prediction of the social complexity hypothesis, i.e., species with more complex social systems will have more complex communication systems.
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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".