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Record W2994764970 · doi:10.14430/arctic69449

Use of Subsistence-Harvested Whale Carcasses by Polar Bears in the Southern Beaufort Sea

2019· article· en· W2994764970 on OpenAlexvenueno aff
Kate Lillie, Eric M. Gese, Todd C. Atwood, Mary M. Conner

Bibliographic record

VenueARCTIC · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersU.S. Bureau of Land ManagementU.S. Air ForceU.S. Department of AgricultureU.S. Fish and Wildlife ServiceUtah State UniversityNational Wildlife Research CenterU.S. Geological SurveyNational Science Foundation
KeywordsUrsus maritimusBeaufort scaleBeaufort seaPopulationSea iceFisherySubsistence agricultureGeographyWhaleOceanographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

The availability of a food subsidy has the potential to influence the condition, behavior, fitness, and population dynamics of a species. Since the early 2000s, monitoring efforts along the coast of northern Alaska have indicated a higher proportion of polar bears (<i>Ursus maritimus</i>) of the southern Beaufort Sea (SB) subpopulation coming onshore to feed on subsistence-harvested bowhead whale (<i>Balaena mysticetus</i>) carcasses during the fall and early winter seasons. Concurrently, Indigenous communities annually hunt bowhead whale and deposit the unused remains at localized “bone piles,” creating the potential for human-bear interactions. Our objective was to determine the annual number of polar bears feeding at the bone pile near Kaktovik, Alaska. Using a hair snag surrounding the bone pile, we collected hair samples to identify individual bears via microsatellite genotypes during 2011 – 14. We used capture-mark-recapture data in the POPAN open-population model to estimate the number of bears visiting the bone pile. We estimated that as many as 72 (SE = 9) and 76 (SE = 10) male and female polar bears, respectively, used the bone pile located at Kaktovik, Alaska, in 2012, which represents approximately 16% of the SB polar bear subpopulation. It will be important to monitor the number of bears using the bone pile and subsequent human-bear interactions and conflicts along the northern coast of Alaska, if sea ice continues to recede.

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 score0.061
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.222
Teacher spread0.197 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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