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Record W1974786591 · doi:10.1007/s10144-005-0231-2

Population ecology of polar bears at Svalbard, Norway

2005· article· en· W1974786591 on OpenAlexafffund
Andrew E. Derocher

Bibliographic record

VenuePopulation Ecology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNorsk PolarinstituttNorges Forskningsråd
KeywordsEcologyArcticBiologyLitterTrophic levelPopulationReproductionVital ratesNorth Atlantic oscillationEcosystemClimate changePolar nightPopulation ecologyDemographyPopulation growthGeography

Abstract

fetched live from OpenAlex

Abstract The population ecology of polar bears at Svalbard, Norway, was examined from 1988 to 2002 using live‐captured animals. The mean age of both females and males increased over the study, litter production rate and natality declined and body length of adults decreased. Dynamics of body mass were suggestive of cyclical changes over time and variation in body mass of both adult females and adult males was related to the Arctic Oscillation index. Similarly, litter production rate and natality correlated with the Arctic Oscillation index. The changes in age‐structure, reproductive rates and body length suggest that recovery from over‐harvest continued for almost 30 years after harvest ended in 1973 and that density‐dependent changes are perhaps being expressed in the population. However, the variation in reproduction and body mass in the population show a relationship between large‐scale climatic variation and the upper trophic level in an Arctic marine ecosystem. Similar change in other polar bear populations has been attributed to climate change, and further research is needed to establish linkages between climate and the population ecology 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 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 score0.045
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.245
Teacher spread0.233 · 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

Citations83
Published2005
Admission routes2
Has abstractyes

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