MétaCan
Menu
Back to cohort

REPERTOIRE, STRUCTURE, AND INDIVIDUAL DISTINCTIVENESS OF THICK-BILLED MURRE CALLS1

2001· article· en· W2155654343 on OpenAlexafffund
Kara L. Lefevre, Anthony J. Gaston, Robert Montgomerie

Bibliographic record

VenueOrnithological Applications · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsQueen's University
FundersNatural Resources CanadaNational Research Centre
KeywordsRepertoireFledgeOptimal distinctiveness theoryBiologyZoologySeasonal breederVocal communicationCall durationVariation (astronomy)Context (archaeology)Animal communicationCommunicationDemographyEcologyHatchingPsychologySocial psychologyAcoustics

Abstract

fetched live from OpenAlex

We describe the vocal repertoires of Thick-billed Murre (Uria lomvia) adults and chicks during the breeding season. Using recordings from throughout the chick-rearing period, we identified four distinct calls of chicks and six of adults. We present sonograms and quantitative descriptions of each call and summarize the behavioral context in which they were used. Chick calls are mostly flute-like sounds at approximately the same pitch that tend to develop from a simple peep during hatching through a rapidly frequency-modulated departure call, given shortly before, during, and after they leave the colony at fledging. Departure calls appear to facilitate interactions between the chick and the attending male parent during this risky period for the chick. Adult calls are lower pitched and sound more gruff, with different call types having significantly different pitch, duration, and number of syllables. Among-individual variation in the crow calls of adults accounts for 44% of the measured variation in this call and indicates the potential for individual recognition, such as the recognition of parents' calls by their chicks, which we have previously documented. Temporal features may form the basis of recognition of adult calls in this species, given that they accounted for twice as much variation as frequency features among individual adults.

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 score0.470
Threshold uncertainty score0.322

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 head0.037
GPT teacher head0.297
Teacher spread0.260 · 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

Citations12
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueOrnithological ApplicationsSame topicAnimal Vocal Communication and BehaviorFrench-language works237,207