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Record W4406095278 · doi:10.58843/ornneo.v35i2.1361

SONGS AND CALLS: PERSPECTIVES ON CREATING A GLOBAL DEFINITION

2025· article· en· W4406095278 on OpenAlexaff
Luis Sandoval, Brendan A. Graham

Bibliographic record

VenueOrnitología Neotropical · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Lethbridge
FundersVicerrectoría de Investigación, Universidad de Costa RicaUniversidad de Costa Rica
KeywordsCategorizationAmbiguityDuration (music)Key (lock)Function (biology)Limit (mathematics)Computer scienceGeographyArtificial intelligenceEvolutionary biologyBiologyMathematics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.306
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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