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Record W7093997896

Prairie Dogs

2023· article· W7093997896 on OpenAlexaboutno aff

Bibliographic record

VenueLincoln (University of Nebraska) · 2023
Typearticle
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsnot available
FundersAnimal and Plant Health Inspection ServiceU.S. Department of Agriculture
KeywordsEndangered speciesWildlifePrairie dogThreatened speciesHabitatWildlife managementWildlife conservationGrasslandHabitat destruction
DOInot available

Abstract

fetched live from OpenAlex

Prairie dogs (Cynomys spp.) occur throughout the prairie states of middle North America from Mexico northward into Canada. They occupy a variety of habitats from prairies to high mountain valleys and sage brush-dominated deserts. The most common species is the black-tailed prairie dog (Cynomys ludovicianus; Figure 1). Prairie dogs are considered a “keystone species.” They provide habitat for many other native, grassland species. Prairie dogs live in colonies or “towns” that can span hundreds to thousands of acres. Depending on the species, their presence is evident by their burrow system. Despite the many ecosystem benefits prairie dogs provide by modifying grasslands, they also create conflicts with people when their activities cause damage. This damage can occur on agricultural lands, as well as in urban and suburban settings. Utah and Mexican prairie dogs are listed as threatened or endangered species and are protected by law. Contact the State wildlife agency and/or the U.S. Fish and Wildlife Service (USFWS) for specific requirements and options regarding damage management methods for these species. If a prairie dog colony contains endangered black-footed ferrets (Mustela nigripes), options for prairie dog control are more restricted. Responsible and professional reduction or elimination of wildlife damage is the goal of wildlife damage management practitioners. This is best accomplished through an integrated approach. No single method is effective in every situation, and success is optimized when damage management is initiated early, consistently, and adaptively using a variety of methods. Because the legality of different methods varies by State, consult local laws and regulations prior to implementing any method. In addition, regulations may require that a survey be conducted to determine if threatened or endangered species are present.

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)0.001
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: none
Teacher disagreement score0.117
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1170.040

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 head0.017
GPT teacher head0.256
Teacher spread0.239 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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