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Record W2898419116 · doi:10.1111/mms.12538

Contact call diversity in natural beluga entrapments in an Arctic estuary: Preliminary evidence of vocal signatures in wild belugas

2018· article· en· W2898419116 on OpenAlexfundno aff
Valeria Vergara, Marie‐Ana Mikus

Bibliographic record

VenueMarine Mammal Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNunavut Wildlife Management BoardQuark Expeditions
KeywordsBeluga WhaleBelugaCetaceaGeographyArcticBiologyCommunicationAcousticsFisheryEcologyZoologyPsychology

Abstract

fetched live from OpenAlex

A bstract Broadband, pulsed contact calls have been described for captive and temporarily restrained belugas, but little information exists on their usage in the wild. We examined vocal production during 14 natural beluga entrapments in a shallow channel in Cunningham Inlet, as isolation events offer ideal contexts to study contact calls. Drone footage, overhead photos, and shore‐based photos confirmed the number of individuals and age composition in each entrapment. Contact calls comprised the majority (61%) of vocalizations produced by entrapped whales compared to the free‐ranging herd (10%). We divided contact calls into complex (80%), those with a stereotyped, spectrographically prominent component overlapping the pulse train that characterizes all beluga contact calls, and simple (20%), those with no overlapping component. For each entrapment, we generated a catalogue of complex contact call types, totaling 87 types. Our classification was corroborated both quantitatively and by 55 naïve human judges. Occasional instances of overlapping contact calls of the same type indicated dyadic production. The number of contact call types per entrapment was strongly related to (never exceeding) the number of individuals, excluding neonates. Although this suggests a system of vocal signatures in belugas, consistent with their fission‐fusion society and earlier findings, whether signature identity is encoded individually or shared with related animals remains unknown.

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)0.001
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 score0.092
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.007
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.267
Teacher spread0.244 · 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

Citations33
Published2018
Admission routes1
Has abstractyes

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