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Record W1545922884 · doi:10.1002/wsb.321

Impacts and management of invasive cool‐season grasses in the Northern Great Plains: Challenges and opportunities for wildlife

2013· article· en· W1545922884 on OpenAlexaff
Susan N. Ellis‐Felege, Cami S. Dixon, Scott D. Wilson

Bibliographic record

VenueWildlife Society Bulletin · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsWildlifeBromus tectorumGrasslandHabitatGeographyEcologyRangelandAgroforestryWildlife conservationVegetation (pathology)Native plantWildlife managementIntroduced speciesInvasive speciesBiology

Abstract

fetched live from OpenAlex

ABSTRACT Grasslands of the Northern Great Plains of North America are in the midst of extensive human‐driven loss and redistribution of important species. Invasive plants contribute to degradation of this ecosystem and present monumental challenges for natural resource managers. Widespread decreases in populations of grassland‐dependent wildlife, particularly birds, have been documented, but relatively little research has been focused on direct responses of wildlife to invading plants relative to native vegetation. Smooth brome ( Bromus inermis ) and Kentucky bluegrass ( Poa pratensis ) are 2 invasive cool‐season grass species found across much of the Northern Great Plains that continue to expand despite management actions intended to reduce them. With eradication unlikely, creativity, cooperation, and science‐based management (e.g., Adaptive Management) are paramount to protect and restore the integrity of grassland habitats across the Northern Great Plains. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.034
GPT teacher head0.225
Teacher spread0.191 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations46
Published2013
Admission routes1
Has abstractyes

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