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Record W4390144777 · doi:10.1111/mms.13095

Geographic variation in simple contact calls of Canadian beluga whales <i>(Delphinapterus leucas</i>)

2023· article· en· W4390144777 on OpenAlexafffundabout
Karyn V. Booy, Valeria Vergara, Lisa L. Loseto, Marie‐Ana Mikus, Marianne Marcoux

Bibliographic record

VenueMarine Mammal Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of ManitobaRaincoast Conservation FoundationFisheries and Oceans Canada
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaAurora Research InstituteFisheries Joint Management CommitteeQuark ExpeditionsGarfield Weston FoundationSeaWorld and Busch Gardens Conservation FundArcticNetUniversity of ManitobaWorld Wildlife Fund
KeywordsBeluga WhaleBelugaLeucasCetaceaGeographyBayVariation (astronomy)ArcticPopulationZoologyBiologyEcologyFisheryDemography

Abstract

fetched live from OpenAlex

Abstract Beluga whales, Delphinapterus leucas , are a highly social species with a complex and diverse vocal repertoire. Although extensively studied and classified, to date few attempts have been made to examine geographic variation in their calls. In this study, we examined geographic variation in simple contact calls (SCCs), specifically those that consist only of broadband pulsed trains, among four Canadian beluga populations from the Eastern Beaufort Sea (EBS), the Eastern High Arctic‐Baffin Bay, St. Lawrence Estuary (SLE), and the Western Hudson Bay. Five acoustic parameters were measured for each call and compared among populations using multivariate discriminant analysis. Results of our study indicate that there is a degree of variation in SCCs among these four populations, with the most geographically distant populations of the SLE and EBS displaying the greatest degrees of dissimilarity in SCC structure relative to geographically closer populations. Further, these results align with genetic variation of Canadian beluga populations previously described in the literature. This study is the first descriptive population comparison of SCCs for beluga and establishes a baseline for continued work into this developing area of research.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.234
Teacher spread0.215 · 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.

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

Citations3
Published2023
Admission routes3
Has abstractyes

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