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Record W2172724705 · doi:10.1139/z06-115

Seasonal and annual movement patterns of polar bears on the sea ice of Hudson Bay

2006· article· en· W2172724705 on OpenAlexafffundvenue
E.K. Parks, Andrew E. Derocher, Nicholas J. Lunn

Bibliographic record

VenueCanadian Journal of Zoology · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsCanadian Wildlife FederationUniversity of Alberta
FundersChurchill Northern Studies Centre
KeywordsUrsus maritimusBaySea icePredationPopulationOceanographyAbundance (ecology)Annual cycleArctic ice packBiologyGeographyEcologyGeologyDemography

Abstract

fetched live from OpenAlex

Polar bears ( Ursus maritimus Phipps, 1774) move thousands of kilometres over sea ice searching for mates and hunting for seals, which are their primary prey. Recently, decreased sea ice extent and earlier ice break-up have been linked to shifts in seal distribution and abundance and to declines in polar bear condition and numbers in the western Hudson Bay polar bear population. We used geographic positioning system and satellite collars deployed between 1991 and 2004 to quantify movement patterns of adult female polar bears on the sea ice of Hudson Bay in relation to reproductive class and temporal variations in sea ice patterns. We tested whether reproductive status and season affected movement and whether temporal changes in movement were correlated with temporal changes in sea ice patterns in Hudson Bay. Movement patterns were not dependent on reproductive status but did change significantly with season. Annual distances moved and areas covered by bears in Hudson Bay have decreased since 1991, which suggests that measured declines in bear condition and numbers are due to reduced prey intake as opposed to increased energy output. These declines in bear movement are correlated with progressively earlier ice break-up in western Hudson Bay.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.946

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)0.0010.000

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 head0.006
GPT teacher head0.174
Teacher spread0.169 · 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

Citations96
Published2006
Admission routes3
Has abstractyes

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