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Record W2167636709 · doi:10.1089/vbz.2014.1703

Transmission and Epidemiology of Bluetongue and Epizootic Hemorrhagic Disease in North America: Current Perspectives, Research Gaps, and Future Directions

2015· review· en· W2167636709 on OpenAlexaff
Mark G. Ruder, Tim Lysyk, David E. Stallknecht, Lane D. Foil, Donna J. Johnson, Christopher Chase, David A. Dargatz, E. Paul J. Gibbs

Bibliographic record

VenueVector-Borne and Zoonotic Diseases · 2015
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicVector-Borne Animal Diseases
Canadian institutionsAgriculture and Agri-Food Canada
FundersU.S. Department of Agriculture
KeywordsEpizooticEpidemiologyTransmission (telecommunications)VirologyDiseaseEnvironmental healthGeographyMedicineOutbreakTelecommunicationsComputer sciencePathology

Abstract

fetched live from OpenAlex

Bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV) are arthropod-transmitted viruses in the genus Orbivirus of the family Reoviridae. These viruses infect a variety of domestic and wild ruminant hosts, although the susceptibility to clinical disease associated with BTV or EHDV infection varies greatly among host species, as well as between individuals of the same species. Since their initial detection in North America during the 1950s, these viruses have circulated in endemic and epidemic patterns, with occasional incursions to more northern latitudes. In recent years, changes in the pattern of BTV and EHDV infection and disease have forced the scientific community to revisit some fundamental areas related to the epidemiology of these diseases, specifically in relation to virus-vector-host interactions and environmental factors that have potentially enabled the observed changes. The aim of this review is to identify research and surveillance gaps that obscure our understanding of BT and EHD in North America.

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)0.001
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.082
GPT teacher head0.350
Teacher spread0.268 · 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

Citations126
Published2015
Admission routes1
Has abstractyes

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