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Record W2419366141 · doi:10.3354/esr00735

Calls of North Atlantic right whales Eubalaena glacialis contain information on individual identity and age class

2016· article· en· W2419366141 on OpenAlexfundno aff
JA McCordic, Holly Root‐Gutteridge, Dana A. Cusano, SL Denes, Susan E. Parks

Bibliographic record

VenueEndangered Species Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceNational Fish and Wildlife FoundationU.S. Fleet Forces CommandU.S. NavyFisheries and Oceans CanadaSyracuse UniversityNational Oceanic and Atmospheric AdministrationUniversity of PennsylvaniaOffice of Naval ResearchPennsylvania State UniversityWoods Hole Oceanographic InstitutionInternational Fund for Animal Welfare
KeywordsRight whaleIdentity (music)WhaleEndangered speciesENCODEGeographyBiologyFisheryZoologyEcologyHabitatGeneticsAcoustics

Abstract

fetched live from OpenAlex

Passive acoustic monitoring is a powerful tool that allows remote detection of marine mammals through their vocalizations. While call detection provides information on species presence, additional information may be contained within the vocalizations that could provide more information regarding the demographics and/or number of individuals in a particular area based on passive acoustic detections. The North Atlantic right whale Eubalaena glacialis produces a stereotyped upswept call, termed the upcall, that is thought to function as a long-distance contact call in this species. As such, the call is likely to contain cues providing information about the individual producing it. The goal of this study was to test whether the right whale upcall could potentially encode information related to the identity and age of the caller. Using upcalls recorded from 14 known individuals through non-invasive suction cup archival acoustic tags, we demonstrate that the upcall does contain sufficient information to discriminate individual identity and age class, with average classification levels of 72.6 and 86.1%, respectively. Parameters measured from the fundamental frequency, duration, and formant structure were most important for discrimination among individuals. This study is the first step in demonstrating the feasibility of obtaining additional data from passive acoustic monitoring to aid in the conservation efforts for this highly endangered species.

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 score0.110
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
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.068
GPT teacher head0.314
Teacher spread0.246 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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