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Record W2165777597 · doi:10.1128/jcm.02582-10

Comparison of Two Multiplex Methods for Detection of Respiratory Viruses: FilmArray RP and xTAG RVP

2011· article· en· W2165777597 on OpenAlexaboutno aff
Kenneth H. Rand, Howard Rampersaud, Herbert Houck

Bibliographic record

VenueJournal of Clinical Microbiology · 2011
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsnot available
FundersUniversity of Florida
KeywordsHuman metapneumovirusVirologyMultiplexMultiplex polymerase chain reactionRespiratory systemVirusMedicineMicrobiologyRespiratory tract infectionsBiologyPolymerase chain reactionBioinformaticsInternal medicineGene

Abstract

fetched live from OpenAlex

We compared the FilmArray RP (Idaho Technology, Inc., Salt Lake City, UT) and the xTAG RVP (Luminex Corporation, Toronto, Canada) multiplex respiratory virus PCR methods for the detection of respiratory viruses in a set of 200 patient specimens frozen at -70 °C after standard viral culture and antigen detection methods were done. Both systems detected between 40 to 50% more viruses than traditional methods, primarily rhinoviruses and human metapneumovirus. The FilmArray RP detected significantly more total viruses either alone or as part of mixed infections than the xTAG RVP, as well as an additional 21.6% more respiratory syncytial viruses. The xTAG RVP requires 5 to 6 h with 2.5 to 3 h of hands-on time, while the FilmArray RP takes about an hour with 3 to 5 min of hands-on time, making it much easier to perform.

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)0.008
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.463
GPT teacher head0.614
Teacher spread0.151 · 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 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

Citations137
Published2011
Admission routes1
Has abstractyes

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