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Record W2017777915 · doi:10.1177/104063870201400516

A Comparison of Polymerase Chain Reaction with and without RNA Extraction and Virus Isolation for Detection of Bovine Viral Diarrhea Virus in Young Calves

2002· article· en· W2017777915 on OpenAlexaffabout
Dirk Deregt, P. S. Carman, Renee Clark, Kimberley M. Burton, W. O. Olson, Scott A. Gilbert

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of GuelphCanadian Food Inspection Agency
Fundersnot available
KeywordsVirologyRNA extractionVirusPolymerase chain reactionBiologyReverse transcriptaseRNAReverse transcription polymerase chain reactionPestivirusDigital polymerase chain reactionMultiplex polymerase chain reactionMultiplexReal-time polymerase chain reactionMolecular biologyViral diseaseGeneFlaviviridaeMessenger RNA

Abstract

fetched live from OpenAlex

Previously, the authors described a multiplex reverse transcriptase-polymerase chain reaction (PCR) assay for detection and typing of bovine viral diarrhea virus (BVDV) from blood of persistently infected (PI) cattle that could be used with or without RNA extraction. In the present study, the PCR assay was evaluated for its ability to detect BVDV in young calves as a screening tool for detection of persistent infections. Both methods, PCR after RNA extraction (rPCR) and the direct method without RNA extraction (dPCR) were applied and compared with virus isolation (VI) with diagnostic specimens. From 450 whole blood samples from Ontario calves, 47 and 39 samples were positive by rPCR and VI, respectively. From the 47 samples positive by rPCR, 45 (96%) also were positive by dPCR when samples were tested both undiluted and diluted 1:10. In comparison to VI, the relative sensitivities of both PCR assays were 100%. Examination of the results indicates that both PCR assays can be used for screening calves for persistent infection with BVDV.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.197

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 head0.054
GPT teacher head0.297
Teacher spread0.242 · 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

Citations29
Published2002
Admission routes2
Has abstractyes

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