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Record W3216570401 · doi:10.1007/s00300-021-02974-6

An on-ice aerial survey of the Kane Basin polar bear (Ursus maritimus) subpopulation

2021· article· en· W3216570401 on OpenAlexafffundabout
Øystein Wiig, Stephen N. Atkinson, Erik W. Born, Seth Stapleton, Todd W. Arnold, Markus Dyck, Kristin L. Laidre, Nicholas J. Lunn, Eric V. Regehr

Bibliographic record

VenuePolar Biology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of AlbertaAlberta Environment and Protected AreasEnvironment and Climate Change CanadaGovernment of Nunavut
FundersRoyal Canadian Mounted PoliceNunavut Wildlife Management BoardMiljø- og FødevareministerietUniversitetet i OsloEnvironment and Climate Change CanadaMinistry of EnvironmentPinngortitaleriffikGovernment of NunavutUniversity of WashingtonWorld Wildlife FundNational Aeronautics and Space Administration
KeywordsUrsus maritimusTransectArcticSea iceAbundance (ecology)BiologyFjordAerial surveyPolarDistance samplingPhysical geographyOceanographyArctic ice packSampling (signal processing)EcologyFisheryGeographyGeologyCartography

Abstract

fetched live from OpenAlex

) to understand how they are affected by the ongoing decrease in Arctic sea ice. The Kane Basin (KB) subpopulation is a group of high-latitude polar bears that ranges between High Arctic Canada and NW Greenland around and north of the North Water polynya (NOW). We conducted a line transect distance sampling aerial survey of KB polar bears during 28 April-12 May 2014. A total of 4160 linear kilometers were flown in a helicopter over fast ice in the fjords and over offshore pack ice between 76° 50' and 80° N'. Using a mark-recapture distance sampling protocol, the estimated abundance was 190 bears (95% lognormal CI: 87-411; CV 39%). This estimate is likely negatively biased to an unknown degree because the offshore sectors of the NOW with much open water were not surveyed because of logistical and safety reasons. Our study demonstrated that aerial surveys may be a feasible method for obtaining abundance estimates for small subpopulations of polar bears.

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 score0.022
Threshold uncertainty score0.999

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)0.0020.000

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 head0.029
GPT teacher head0.274
Teacher spread0.245 · 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

Citations6
Published2021
Admission routes3
Has abstractyes

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