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Record W4390792648 · doi:10.1177/10406387231223290

Rapid differentiation of infectious salmon anemia virus avirulent (HPR0) from virulent (HPRΔ) variants using multiplex RT-qPCR

2024· article· en· W4390792648 on OpenAlexfundno aff
Thomas F. Rounsville, Mark P. Polinski, Alyssa G. Marini, Sarah M. Turner, Niccolò Vendramin, Argelia Cuenca, Michael Pietrak, Brian C. Peterson, Deborah A. Bouchard

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsnot available
FundersAnimal and Plant Health Inspection ServiceAgricultural Research ServiceFisheries and Oceans CanadaU.S. Department of Agriculture
KeywordsVirulenceVirologyBiologyMultiplexEquine infectious anemiaVirusMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

L.). ISA outbreaks have resulted in significant losses of farmed salmon globally, often with a sudden onset. However, 2 phenotypically distinct variants of ISAV exist, each with divergent disease outcomes, associated regulations, and control measures. ISAV-HPRΔ, also known as ISAV-HPR deleted, is responsible for ISA outbreaks; ISAV-HPR0, is avirulent and is not known to cause fish mortality. Current detection methodology requires genetic sequencing of ISAV-positive samples to differentiate phenotypes, which may slow responses to disease management. To increase the speed of phenotypic determinations of ISAV, we developed a new, rapid multiplex RT-qPCR method capable of 1) detecting if a sample contains any form of ISAV, 2) discriminating whether positive samples contain HPRΔ or HPR0, and 3) validating RNA extractions with an internal control, all in a single reaction. Following assay development and optimization, we validated this new multiplex on 31 ISAV strains collected from North America and Europe (28 ISAV-HPRΔ, 3 ISAV-HPR0). Finally, we completed an inter-laboratory comparison of this multiplex qPCR with commercial ISAV testing and found that both methods provided equivalent results for ISAV detection.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.455
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.030
GPT teacher head0.262
Teacher spread0.232 · 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 designBench or experimental
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

Citations7
Published2024
Admission routes1
Has abstractyes

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