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Record W2520320138 · doi:10.1111/mms.12357

Satellite telemetry reveals population specific winter ranges of beluga whales in the Bering Sea

2016· article· en· W2520320138 on OpenAlexaff
John J. Citta, Pierre Richard, Lloyd F. Lowry, Gregory O’Corry-Crowe, Marianne Marcoux, Robert Suydam, Lori Quakenbush, Roderick C. Hobbs, Д. И. Литовка, Kathryn J. Frost, T. G. Gray, Jack Orr, Ben Tinker, Helen Aderman, Matthew L. Druckenmiller

Bibliographic record

VenueMarine Mammal Science · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsBeluga WhaleBelugaBayPopulationBeaufort seaGeographyFisheryOceanographyAerial surveyLeucasMarine mammalSea iceArcticBiologyGeologyRemote sensingMeteorologyDemography

Abstract

fetched live from OpenAlex

Abstract At least five populations (stocks) of beluga whales ( Delphinapterus leucas ) are thought to winter in the Being Sea, including the Bristol Bay, Eastern Bering Sea (Norton Sound), Anadyr, Eastern Chukchi Sea, and Eastern Beaufort Sea (Mackenzie) populations. Belugas from each population have been tagged with satellite‐linked transmitters, allowing us to describe their winter (January–March) distribution. The objectives of this paper were to determine: (1) If each population winters in the Bering Sea, and if so, where? (2) Do populations return to the same area each year ( i.e ., are wintering areas traditional)? (3) To what extent do the winter ranges of different populations overlap? Tagged belugas from all five populations either remained in, or moved into, the Bering Sea and spent the winter there. Each population wintered in a different part of the Bering Sea and populations with multiple years of data (four of five) returned to the same regions in multiple years. When data were available from two populations that overlapped in the same year, they did not occupy the shared area at the same time. Although our sample sizes were small, the evidence suggests belugas from different populations have traditional winter ranges that are mostly exclusive to each population.

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)0.002
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 score0.232
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.001
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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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

Citations45
Published2016
Admission routes1
Has abstractyes

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