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West Nile virus: North American experience

2011· review· en· W1977538191 on OpenAlexaboutno aff
Erik K. Hofmeister

Bibliographic record

VenueIntegrative Zoology · 2011
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
Fundersnot available
KeywordsFlavivirusWest Nile virusEpizooticJapanese encephalitisVirologyPopulationVirusDengue feverDengue virusGeographyFlaviviridaeEncephalitisBiologyViral diseaseMedicineEnvironmental health

Abstract

fetched live from OpenAlex

West Nile virus, a mosquito-vectored flavivirus of the Japanese encephalitis serogroup, was first detected in North America following an epizootic in the New York City area in 1999. In the intervening 11 years since the arrival of the virus in North America, it has crossed the contiguous USA, entered the Canadian provinces bordering the USA, and has been reported in the Caribbean islands, Mexico, Central America and, more recently, South America. West Nile virus has been reported in over 300 species of birds in the USA and has caused the deaths of thousands of birds, local population declines of some avian species, the clinical illness and deaths of thousands of domestic horses, and the clinical disease in over 30 000 Americans and the deaths of over 1000. Prior to the emergence of West Nile virus in North America, St. Louis encephalitis virus and Dengue virus were the only other known mosquito-transmitted flaviviruses in North America capable of causing human disease. This review will discuss the North American experience with mosquito-borne flavivirus prior to the arrival of West Nile virus, the entry and spread of West Nile virus in North America, effects on wild bird populations, genetic changes in the virus, and the current state of West Nile virus transmission.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.044
GPT teacher head0.363
Teacher spread0.320 · 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

Citations28
Published2011
Admission routes1
Has abstractyes

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