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Ecotypic variation affects the conservation of North American badgers endangered along their northern range extent

2018· book· en· W2791662277 on OpenAlexaboutno aff
Richard D. Weir, Trevor A. Kinley, Richard Klafki, Clayton D. Apps

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyEcologyRange (aeronautics)Endangered speciesPredationHome rangeBiologyHabitat

Abstract

fetched live from OpenAlex

This chapter is based on ecological information on 82 radio-tagged badgers (39 F, 43 M) among three study populations in British Columbia, Canada between 1996 and 2010, data that were collected to learn more about the ecology of badgers and consider how variation in their ecology might inform regional conservation strategies. The widely spaced, lower density prey and distribution of soil deposits suitable for digging in British Columbia likely required badgers to use substantially larger areas, relative to the core range, in which to acquire sufficient energy to survive and reproduce. Strikes from automobiles were the primary cause of death among all radio-tagged badgers and this source of mortality is pervasive throughout the limited distribution of badgers in British Columbia. Despite their potential for high fecundity, populations of badgers in British Columbia likely remain at considerable risk compared to those in the core of the species’ range.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.344

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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

Citations29
Published2018
Admission routes1
Has abstractyes

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