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Record W1564957701 · doi:10.22621/cfn.v118i3.12

Observations of Habitat Use by Polar Bears, <em>Ursus maritimus</em>, in the Alaskan Beaufort, Chukchi, and Northern Bering Seas

2004· article· en· W1564957701 on OpenAlexvenueno aff
Donald J. Hansen

Bibliographic record

VenueThe Canadian Field-Naturalist · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersU.S. Department of the Interior
KeywordsUrsus maritimusBeaufort scaleBeaufort seaGeographySea iceFisheryOceanographyWhaleHabitatAerial surveyArcticEcologyGeologyBiologyMeteorologyCartography

Abstract

fetched live from OpenAlex

A total of 1112 Polar Bears (Ursus maritimus) at 482 sightings were recorded during aerial surveys in the Beaufort, Chukchi, and northern Bering Seas conducted primarily during September and October from 1979-1999. Of these bears, 784 were observed offshore at 400 sightings. The surveys were conducted by the Naval Ocean Systems Center and Minerals Management Service; they were designed to monitor the fall Bowhead Whale (Balaena mysticetus) migration. Over the 20-year period, 1,096,620 kilometers of surveys were flown. The majority of the offshore Polar Bears, 595 bears at 290 sightings, and most of the kill sites and polar bear tracks were recorded in 80-100% ice cover. The number of bears per kilometer increased substantially in >24% ice cover, with the highest number observed in 80-100% ice cover. This habitat use probably is related to the availability of seals, their primary prey. There were 328 bears (83 sightings) recorded on land, and most of them were associated with whale carcasses and bowhead whale subsistence harvest sites along the Alaskan Beaufort Sea coast.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.206
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.018
GPT teacher head0.213
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2004
Admission routes1
Has abstractyes

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