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Record W4389789037 · doi:10.1101/2023.12.13.23298992

A multiplex qRT-PCR assay for detection of Influenza A and H5 subtype targeting new SNPs present in high pathogenicity avian influenza Canadian 2022 outbreak strains

2023· preprint· en· W4389789037 on OpenAlexafffundabout
Tracy D. Lee, Frankie Tsang, Kathleen Kolehmainen, Natalie Prystajecky, Agatha N. Jassem, John R. Tyson

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of British ColumbiaBC Centre for Disease Control
FundersBritish Columbia Centre for Disease ControlCanadian Food Inspection Agency
KeywordsInfluenza A virus subtype H5N1MultiplexSubtypingOutbreakVirologyMultiplex polymerase chain reactionBiologyPathogenicityHighly pathogenicSeasonal influenzaInfluenza A virusComputational biologyGenePolymerase chain reactionGeneticsVirusMicrobiologyMedicineCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Computer science

Abstract

fetched live from OpenAlex

Abstract H5N1 is a highly pathogenic avian Influenza A subtype that has been known to also infect mammalian hosts and presents a potential public health risk. To address and mitigate the affects of new SNPs, found in recent Canadian outbreaks, on diagnostic detection we developed two qRT-PCR assays by modifying current probes to match sequences detected in the east and west coast of Canada. These assays were multiplexed with a third qRT-PCR assay targeting the M segment, allowing streamlined detection of Influenza A and subtyping for H5. This three-plex qRT-PCR was validated by assessing analytical specificity, limit-of-detection, precision, and accuracy.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.979
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.119
GPT teacher head0.367
Teacher spread0.248 · 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 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

Citations2
Published2023
Admission routes3
Has abstractyes

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Same venuemedRxiv→Same topicInfluenza Virus Research Studies→French-language works237,207→