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Record W3168802705 · doi:10.14430/arctic72532

Do Wild Polar Bears (<i>Ursus maritimus</i>) Use Tools When Hunting Walruses (<i>Odobenus rosmarus</i>)?

2021· article· en· W3168802705 on OpenAlexafffundvenueabout
Ian Stirling, Kristin L. Laidre, Erik W. Born

Bibliographic record

VenueARCTIC · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsEnvironment and Climate Change Canada
FundersDirectorate for Biological SciencesEnvironment and Climate Change CanadaUniversity of AlbertaPinngortitaleriffik
KeywordsUrsus maritimusUrsusCaptivityGeographyEcologyZoologyArchaeologyBiologyArcticPopulation

Abstract

fetched live from OpenAlex

Since the late 1700s, reports of polar bears (Ursus maritimus) using tools (i.e., pieces of ice or stones) to kill walruses (Odobenus rosmarus) have been passed on verbally to explorers and naturalists by their Inuit guides, based on local traditional ecological knowledge (TEK) as well as accounts of direct observations or interpretations of tracks in the snow made by the Inuit hunters who reported them. To assess the possibility that polar bears may occasionally use tools to hunt walruses in the wild, we summarize 1) observations described to early explorers and naturalists by Inuit hunters about polar bears using tools, 2) more recent documentation in the literature from Inuit hunters and scientists, and 3) recent observations of a polar bear in a zoo spontaneously using tools to access a novel food source. These observations and previously published experiments on brown bears (Ursus arctos) confirm that, in captivity, polar and brown bears are both capable of conceptualizing the use of a tool to obtain a food source that would otherwise not be accessible. Based on the information from all our sources, this may occasionally also have been the case in the wild. We suggest that possible tool use by polar bears in the wild is infrequent and mainly limited to hunting walruses because of their large size, difficulty to kill, and their possession of potentially lethal weapons for both their own defense and the direct attack of a predator.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.028
GPT teacher head0.236
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2021
Admission routes4
Has abstractyes

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