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Record W1906963568 · doi:10.1002/dneu.22348

Vocal matching and intensity of begging calls are associated with a forebrain song circuit in a generalist brood parasite

2015· article· en· W1906963568 on OpenAlexaff
Wan‐Chun Liu, James W. Rivers, David J. White

Bibliographic record

VenueDevelopmental Neurobiology · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsWilfrid Laurier University
FundersAnimal Behavior Society
KeywordsBrood parasiteBiologyBeggingForebrainCowbirdVocal learningAltricialGeneralist and specialist speciesSongbirdNeuroscienceZoologyEcologyHost (biology)Parasitism

Abstract

fetched live from OpenAlex

Vocalizations produced by developing young early in life have simple acoustic features and are thought to be innate. Complex forms of early vocal learning are less likely to evolve in young altricial songbirds because the forebrain vocal-learning circuit is underdeveloped during the period when early vocalizations are produced. However, selective pressure experienced in early postnatal life may lead to early vocal learning that is likely controlled by a simpler brain circuit. We found the food begging calls produced by fledglings of the brown-headed cowbird (Molothrus ater), a generalist avian brood parasite, induced the expression of several immediate early genes and early circuit innervation in a forebrain vocal-motor pathway that is later used for vocal imitation. The forebrain neural activity was correlated with vocal intensity and variability of begging calls that appears to allow cowbirds to vocally match host nestmates. The begging-induced forebrain circuits we observed in fledgling cowbirds were not detected in nonparasitic passerines, including species that are close relatives to the cowbird. The involvement of forebrain vocal circuits during fledgling begging and its association with vocal learning plasticity may be an adaptation that provides young generalist brood parasites with a flexible signaling strategy to procure food from a wide range of heterospecific host parents.

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 score0.297
Threshold uncertainty score0.443

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 head0.046
GPT teacher head0.258
Teacher spread0.212 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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