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Record W3126683878 · doi:10.3354/meps13642

Polar bear Ursus maritimus use of the western Hudson Bay flaw lead

2021· article· en· W3126683878 on OpenAlexaff
EM Henderson, Andrew E. Derocher, Nicholas J. Lunn, Benoît Montpetit, EH Merrill, ES Richardson

Bibliographic record

VenueMarine Ecology Progress Series · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Alberta
Fundersnot available
KeywordsUrsus maritimusBayPredationArcticSea iceHabitatOpen waterOceanographyPelagic zoneGeographyEcologyEnvironmental scienceForagingPhysical geographyFisheryGeologyBiology

Abstract

fetched live from OpenAlex

Flaw leads (FLs) and polynyas are recurrent areas of open water within sea ice that provide habitat for a diversity of Arctic species. The western Hudson Bay FL is a major, predictable habitat feature; however, its importance to polar bears Ursus maritimus has not been examined. We mapped the FL using synthetic aperture radar (resolution 62.3 × 121 m) from December to May, 2009-2018, and assessed FL use by 73 adult female polar bears tracked using satellite telemetry. Maximum FL width varied from 4 km in March to 145 km in May. Bears were closest to the FL in May, which coincided with their hyperphagic period and the seal pupping season. Only 31.5% (n = 23) of the bears used the FL, and they travelled faster, with lower turning angles along the FL (16° turns at 101° and -69° relative to the FL), suggesting the feature acted as a corridor that could increase prey encounters. Bears were closer to and crossed sections of the FL that were 68% narrower than those not crossed, indicating that a wider FL deters crossing. Abundant prey likely attracts some bears to the FL, but most bears avoid the FL between hunts, likely to conserve energy on consolidated ice or to reduce intraspecific interactions. Increases in open water resulting from climate warming might make the FL more challenging for bears to cross, but could make it more attractive if open-water prey densities increase.

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 score0.195
Threshold uncertainty score0.997

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.004
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.235
Teacher spread0.216 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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