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EVALUATION OF COMMERCIAL ASSAYS FOR DETECTING WEST NILE VIRUS ANTIGEN

2006· article· en· W2107171401 on OpenAlexaffabout
Kristen L. Burkhalter, L. Robbin Lindsay, Robert Anderson, Antonia Dibernardo, Whalley K. Fong, Roger S. Nasci

Bibliographic record

VenueJournal of the American Mosquito Control Association · 2006
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsResponse Biomedical (Canada)University of WinnipegPublic Health Agency of Canada
FundersPublic Health Agency
KeywordsVirologyBiologyWest Nile virusFlavivirusVirusFlaviviridaeArbovirusEncephalitisAntigenReverse transcriptasePolymerase chain reactionViral diseaseImmunology

Abstract

fetched live from OpenAlex

Two commercially available West Nile virus (WNV) detection assays (RAMP WNV test, Response Biomedical Corp., Burnaby, British Columbia, Canada; and VecTest WNV antigen assay, Medical Analysis Systems, Inc., Camarillo, CA) were compared for sensitivity, specificity, and ability to detect WNV in field-collected mosquito pools. Serially diluted stock seed WNV and St. Louis encephalitis virus (SLEV) were used to determine sensitivity and specificity. The RAMP WNV test detected WNV at concentrations as low as 3.17 log10 plaque-forming units per milliliter (PFU/ml), whereas the VecTest assay detected WNV at concentrations as low as 5.17 log10 PFU/ml. Neither test cross-reacted with SLEV. A WNV-specific reverse transcriptase polymerase chain reaction was used to identify positives among field-collected mosquito pools. The RAMP WNV test detected 94% of positive pools and the VecTest assay detected 65% of the positive field-collected pools. Despite these differences, both assays have characteristics that make them useful in WNV surveillance programs.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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

Citations43
Published2006
Admission routes2
Has abstractyes

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