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Record W2026533084 · doi:10.1080/00207233.2013.801628

Conservation and management of large carnivores in North America

2013· article· en· W2026533084 on OpenAlex
Sterling D. Miller, Bruce N. McLellan, Andrew E. Derocher

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Environmental Studies · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of AlbertaGovernment of British Columbia
FundersU.S. Bureau of Land Management
KeywordsUngulateWildlifeGeographyCarnivoreExtinction (optical mineralogy)Distribution (mathematics)Wildlife managementEcologyHabitatWildlife conservationRange (aeronautics)PredationFlagship speciesEndangered speciesBiology

Abstract

fetched live from OpenAlex

Between the eighteenth and twentieth centuries in North America, large carnivores were significantly reduced in numbers and distribution. Wildlife management priorities changed during the last century to emphasize recovery and conservation with benefits to all species. Populations of large carnivores are likely to persist and expand into new areas within their original range where habitats are both socially and biologically suitable. Polar bears (Ursus maritimus) are an exception to this pattern as major contractions in numbers and distribution caused by global warming are now unavoidable. The extinction of polar bears during the twenty-first century is possible without great reductions in atmospheric greenhouse gases. Conservation and management of large carnivores is complicated because they require large landscapes, they may compete with hunters for ungulate prey, they can adversely impact economic activities such as livestock operations, and they sometimes, although rarely, attack and kill people.

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.

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 score0.027
Threshold uncertainty score0.864

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 science0.0000.001
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 head0.013
GPT teacher head0.253
Teacher spread0.240 · 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