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Record W4381611982 · doi:10.1139/as-2023-0004

Post-conflict movements of polar bears in western Hudson Bay, Canada

2023· article· en· W4381611982 on OpenAlexafffundvenueabout
Erin N. Miller, Vicki Trim, Nicholas J. Lunn, David McGeachy, Andrew E. Derocher

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsEnvironment and Climate Change CanadaAgriculture Food and Rural DevelopmentUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChurchill Northern Studies CentreUniversity of AlbertaEnvironment and Climate Change CanadaCanadian Wildlife FederationWorld Wildlife FundParks CanadaQuark Expeditions
KeywordsBayUrsus maritimusCarnivoreUrsusGeographyClimate changeDemographyEcologyArcticPredationBiologyArchaeologyPopulationSociology

Abstract

fetched live from OpenAlex

Human–carnivore conflicts have increased as habitat has been affected by development and climate change. Understanding how biological factors, environment, and management decisions affect the behaviour of animals may reduce conflicts. We examined how biological factors, sea ice conditions, and management decisions affected the autumn migratory movement of polar bears ( Ursus maritimus Phipps, 1774) from 2016 to 2021 following their capture near Churchill, Manitoba, Canada, and release after a mean of 20 days (SE 2) in a holding facility. We deployed eartag satellite transmitters on 63 bears (26 males, 37 females), with 49% adults (>5 years old), 48% subadults (3–5 year old), and 3% <2-year old. We compared variation in on-ice departure of bears released post-conflict (conflict) to adult females without a conflict history (non-conflict). Conflict bears departed 89 km further north (mean = 59.7°N, SE 0.2) of non-conflict bears (mean = 58.9°N, SE 0.1). Bears released later during the migratory period were less likely to re-enter a community at a rate of 5.9%–6.4% per day. Of 69 releases (6 individuals requiring multiple releases), 12 bears re-entered Churchill and 13 entered Arviat, Nunavut. We suggest that the holding facility was effective at preventing additional conflicts and individuals with a high likelihood of recidivism should be held longer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.249
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2023
Admission routes4
Has abstractyes

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