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Record W4406569857 · doi:10.58843/ornneo.v35i2.693

THE STUDY OF BIRD VOCALIZATIONS IN NEOTROPICAL HABITATS: CURRENT KNOWLEDGE AND FUTURE STEPS

2025· article· en· W4406569857 on OpenAlexaff
Luis Sandoval, Brendan A. Graham, J. Roberto Sosa‐López, Oscar Laverde-R., Yimen G. Araya‐Ajoy

Bibliographic record

VenueOrnitología Neotropical · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Lethbridge
FundersUniversidad de Costa Rica
KeywordsCurrent (fluid)HabitatGeographyEcologyBiologyGeologyOceanography

Abstract

fetched live from OpenAlex

Research on avian bioacoustics in the Neotropics has surged over the last several decades due to increased interest in the large diversity of vocal behaviors and vocalization and the broader accessibility of recording equipment and software. Here, we present a synthesis of the current and past knowledge of Neotropical bird bioacoustics. This synthesis is the result of the symposium "Bioacoustics in the Neotropics", organized for the XI Neotropical Ornithological Congress in San Jose, Costa Rica, in July 2019. We covered what we consider the main topics in avian bioacoustics that have been studied in this region over the last 30 years. Our review includes repertoire descriptions, geographic variation, diversity in vocal behaviors, seasonality, duetting, genetic association, and playback experiments. Additionally, we present information for what we believe may be the main veins of investigation for the coming future in the Neotropics, considering the large diversity of species that are found in the region and the new investigations developed in other geographic areas. We expect this review to work as a summary of the current literature and a guide to stimulate future research in important areas within the field of avian bioacoustics in the Neotropics.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.333

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 head0.015
GPT teacher head0.331
Teacher spread0.316 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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