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Record W2507596979 · doi:10.1002/jmv.24680

Droplet digital PCR to investigate quasi‐species at codons 119 and 275 of the A(H1N1)pdm09 neuraminidase during zanamivir and oseltamivir therapies

2016· article· en· W2507596979 on OpenAlexaff
Yacine Abed, Julie Carbonneau, Arnaud G. L’Huillier, Laurent Kaiser, Guy Boivin

Bibliographic record

VenueJournal of Medical Virology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsZanamivirNeuraminidaseOseltamivirVirologyDigital polymerase chain reactionReverse transcriptaseBiologyNeuraminidase inhibitorVirusMolecular biologyGenePolymerase chain reactionMedicineGeneticsCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

The H275Y and E119D neuraminidase (NA) mutations constitute important molecular markers of resistance to NA inhibitors in A(H1N1) pdm09 viruses. We used reverse transcriptase-droplet digital PCR amplification (RT-ddPCR) to analyze quasi-species at codons 275 and 119 of the NA in A(H1N1) pdm09 viruses recovered from an immuncompromised patient who received oseltamivir and zanamivir therapies. RT-ddPCR assays detected and quantified H275Y and E119D mutations with an efficiency that was comparable to that of high throughput sequencing (HiSeq 2500 Illumina, San Diego, CA) technology. With its sensitivity and reproducibility, RT-ddPCR could be a reliable method for accurate detection and quantification of major NAI-resistance mutations in clinical settings. J. Med. Virol. 89:737-741, 2017. © 2016 Wiley Periodicals, Inc.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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