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Record W3016007874 · doi:10.1101/2020.04.06.028902

Optimization of SARS-CoV-2 detection by RT-QPCR without RNA extraction

2020· preprint· en· W3016007874 on OpenAlexaff
Natacha Mérindol, Geneviève Pépin, Caroline Marchand, Marylène Rheault, Christine Peterson, André Poirier, Hugo Germain, Alexis Danylo

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsUniversité de MontréalUniversité du Québec à Trois-RivièresCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-Québec
Fundersnot available
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)RNA extractionExtraction (chemistry)RNADetection limitCoronavirus disease 2019 (COVID-19)VirologyReal-time polymerase chain reaction2019-20 coronavirus outbreakBiologyChromatographyChemistryMedicineGeneBiochemistryPathology

Abstract

fetched live from OpenAlex

Abstract Rapid and reliable screening of SARS-CoV-2 is fundamental to assess viral spread and limit the pandemic we are facing. In this study we evaluated the reliability and the efficiency of a direct RT-QPCR method (without RNA extraction) using SeeGene Allplex™ 2019-nCoV RT-QPCR and the influence of swab storage media composition on further viral detection. We show that SeeGene’s assay provides similar efficiency as the RealStar ® SARS-CoV-2 RT-PCR kit (Altona Diagnostics), and that RNA extraction is not necessary nor advantageous if samples are stored in UTM or molecular water but is recommended if samples are stored in saline solution and in Hanks medium.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.113
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.038
GPT teacher head0.281
Teacher spread0.243 · 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.

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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

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