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Record W1651541554 · doi:10.22230/jem.2010v10n3a4

British Columbia's Southern Interior: Badger Wildlife Habitat Decision Aid

2010· article· en· W1651541554 on OpenAlexfundaboutno aff
Richard D. Weir, Pedro Lara Almuedo

Bibliographic record

VenueJournal of Ecosystems and Management · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersMinistry of EnvironmentThompson Rivers University
KeywordsWildlifeBadgerHabitatGeographyEcologyEndangered speciesForest managementSilvicultureWildlife managementRange (aeronautics)Environmental resource managementWildlife conservationAgroforestryForestryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Under the Forest and Range Practices Act, forest and range licensees in British Columbia are required to develop Forest Stewardship Plans and manage their operations to maintain limiting habitats of Identified Wildlife within their tenures. North American badgers (Taxidea taxus) are large members of the weasel family that are a Species At Risk within the Identified Wildlife Management Strategy (IWMS) and are listed as Endangered by COSEWIC. Several aspects of their ecology make them susceptible to forest and range management activities, including their dependence on the grassland, open forest, and modified forested habitat that supports their prey. This Wildlife Habitat Decision Aid (WHDA) summarizes the latest scientific and experiential information that forest and range managers, including silviculture planners, operational foresters, and ranchers, need to consider when managing for badger habitat requirements. This information was obtained through a literature review and discussions with researchers studying badger ecology in British Columbia.The WHDA format has been used to convey information on factors requiring consideration when managing forests and range in British Columbia for specific wildlife species. This WHDA provides information on habitat features needed by badgers for reproductive dens, resting sites, and foraging habitats; biogeoclimatic zones where badgers occur; and considerations when conducting harvesting, silviculture activities, or livestock grazing in badger range. We provide a map of the distribution and list the biogeoclimatic zones in which badgers occur to help users identify where to apply management considerations. Also included is a valuable resource and reference list that contains more detailed information. Most reference material that is not available online can be ordered through libraries.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.229
Threshold uncertainty score0.461

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.000
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0400.006

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 head0.005
GPT teacher head0.191
Teacher spread0.187 · 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 designSimulation or modeling
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

Citations1
Published2010
Admission routes2
Has abstractyes

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