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Record W3209652510 · doi:10.1093/jipm/pmab029

Stable Fly (Diptera: Muscidae)—Biology, Management, and Research Needs

2021· article· en· W3209652510 on OpenAlexaff
Kateryn Rochon, Jerome A. Hogsette, Phillip E. Kaufman, Pia U. Olafson, Sonja L. Swiger, David B. Taylor

Bibliographic record

VenueJournal of Integrated Pest Management · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsUniversity of Manitoba
FundersNational Institute of Food and AgricultureU.S. Department of Agriculture
KeywordsStomoxysMuscidaeStable flyLivestockBiologyEphemeral keyIntegrated pest managementAgricultureEcologyEnvironmental resource managementAgroforestryEnvironmental planningGeography

Abstract

fetched live from OpenAlex

Abstract Stable flies, Stomoxys calcitrans (L.) are global pests of livestock, companion animals, and humans. These flies inflict painful bites and cause significant economic losses to producers by reducing livestock production. In addition, they have been associated with the mechanical transmission of several pathogens causing disease in animals. Management of this species is difficult because: 1) their developmental habitats are often ephemeral accumulations of decomposing vegetation, 2) they can exploit cultural practices in many agricultural and urban environments, and 3) the adults are highly mobile. An integrated pest management (IPM) approach is required to effectively manage stable flies, including integration of cultural, mechanical, physical, biological, and chemical control options. The challenges of stable flies in different animal commodities are discussed, and current and novel technologies for control are presented. Lastly, need for additional research to improve stable fly management methods are discussed.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.288
Teacher spread0.252 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations67
Published2021
Admission routes1
Has abstractyes

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