MétaCan
Menu
Back to cohort

Immunoassay Targeting Nonstructural Protein 5 To Differentiate West Nile Virus Infection from Dengue and St. Louis Encephalitis Virus Infections and from Flavivirus Vaccination

2003· article· en· W2045897139 on OpenAlexaff
Susan J. Wong, Rebekah H. Boyle, Valerie L. Demarest, Anh N. Woodmansee, Laura D. Kramer, Hongmin Li, Michael Drebot, Raymond A. Koski, Erol Fikrig, Denise A. Martin, Pei‐Yong Shi

Bibliographic record

VenueJournal of Clinical Microbiology · 2003
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsHealth Canada
FundersNational Institute of Allergy and Infectious DiseasesCenters for Disease Control and PreventionNational Institutes of Health
KeywordsFlavivirusVirologyDengue virusDengue feverJapanese encephalitisFlaviviridaeNS3SerologyVaccinationEncephalitisZika virusBiologyVirusAntibodyImmunoassayDengue vaccineViral diseaseImmunologyHepatitis C virus

Abstract

fetched live from OpenAlex

West Nile virus (WNV) is an emerging flavivirus that has caused frequent epidemics since 1996. Besides natural transmission by mosquitoes, WNV can also be transmitted through blood transfusion and organ transplantation, thus heightening the urgency of development of a specific and rapid serologic assay of WNV infection. The current immunoassays lack specificity because they are based on detection of antibodies against WNV structural proteins and immune responses to structural proteins among flaviviruses cross-react to each other. Here, we describe microsphere immunoassays that detect antibodies to nonstructural proteins 3 and 5 (NS3 and NS5). In contrast to immunoassays based on viral envelope and NS3 proteins, the NS5-based assay (i) reliably discriminates between WNV infections and dengue virus or St. Louis encephalitis virus infections, (ii) differentiates between flavivirus vaccination and natural WNV infection, and (iii) indicates recent infections. These unique features of the NS5-based immunoassay will be very useful for both clinical and veterinary diagnosis of WNV infection.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.603
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.318
Teacher spread0.303 · 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 teacher head, 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

Citations121
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Clinical MicrobiologySame topicMosquito-borne diseases and controlFrench-language works237,207