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Record W2049943486 · doi:10.3138/jvme.30.2.143

West Nile Virus: Emerging Threat to Public Health and Animal Health

2003· article· en· W2049943486 on OpenAlexvenueno aff
Robert G. McLean

Bibliographic record

VenueJournal of Veterinary Medical Education · 2003
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
Fundersnot available
KeywordsWest Nile virusPublic healthEnvironmental healthAnimal healthVirologyMedicineVeterinary medicineVirusNursing

Abstract

fetched live from OpenAlex

West Nile virus (WNV) is in the genus Flavivirus, family Flavioiridae, and is closely related to other members of this genus: Japanese encephalitis virus in Southeast Asia, Murray Valley encephalitis virus in Australia, and St. Louis encephalitis (SLE) virus in North and South America. The principal vertebrate hosts for these arthropod-borne viruses (arboviruses) are wild birds, and the primary vectors are mosquitoes. Little clinical disease or mortality has been reported previously in wild birds from natural infection with these viruses, although significant morbidity and mortality has occurred in humans and domestic animals. West Nile virus (WNV) previously occurred throughout Africa, Middle East, Europe, and the western parts of Asia and was introduced into the United States in New York City (NYC) in 1999. It is still unknown how WNV entered the US, but it quickly became established, causing a human epidemic of 62 cases and an epizootic in the regional bird population, mostly in American crows. The WNV strain introduced was virulent for North American birds and caused significant mortality in crows and related species. This bird mortality was unusual for arboviruses but quickly became a useful sentinel for public health officials to detect the presence of WNV.

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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.070
GPT teacher head0.414
Teacher spread0.344 · 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
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

Citations9
Published2003
Admission routes1
Has abstractyes

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