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Record W3141461406 · doi:10.1139/as-2019-0031

Spatio-temporal summer distribution of Cumberland Sound beluga whales (<i>Delphinapterus leucas</i>) in Clearwater Fiord, Nunavut, Canada

2021· article· en· W3141461406 on OpenAlexaffvenueabout
Karyn V. Booy, Xavier Mouy, Steven H. Ferguson, Marianne Marcoux

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of VictoriaUniversity of ManitobaFisheries and Oceans Canada
Fundersnot available
KeywordsFjordBelugaBeluga WhaleLeucasAerial surveySound (geography)Threatened speciesGeographyOceanographyFisheryHabitatEcologyGeologyCartographyArcticBiology

Abstract

fetched live from OpenAlex

The Cumberland Sound (Nunavut, Canada) beluga whale (Delphinapterus leucas (Pallas, 1776)) population has been designated as threatened and updated biological information about summer distribution is required for a sound recovery plan. Variation in aerial survey counts are speculated to occur due to movement of belugas in and out of the fiord, and there is still uncertainty related to their distribution within key summer habitat. To address these knowledge gaps, non-invasive passive acoustic monitoring (PAM) systems were deployed in August of 2010 and 2011. An automated detector was used to determine presence/absence and quantify calls by recorder site. Results were verified by partial manual analysis of 20% of the files. The detector had a minimum accuracy of 85% for presence/absence and 42% for call quantification. Belugas were detected primarily at the uppermost site of Clearwater Fiord, with detections subsiding with increasing proximity to the fiord entrance. Diel variation in call patterns were quantified at two separate sites in different years, but no correlation was observed between tidal cycles and number of detections. This study indicates that Cumberland Sound beluga may prefer sites at the head of Clearwater Fiord. Further research is required to identify which environmental variables contribute to this observed summer distribution.

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 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 score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.019
GPT teacher head0.241
Teacher spread0.223 · 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

Citations7
Published2021
Admission routes3
Has abstractyes

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