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Record W3134183039 · doi:10.1371/journal.pone.0247799

Genomic characterization and evolution of SARS-CoV-2 of a Canadian population

2021· article· en· W3134183039 on OpenAlexaffabout
Manna Zhang, Lin Li, Ma Luo, Binhua Liang

Bibliographic record

VenuePLoS ONE · 2021
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsPublic Health Agency of CanadaUniversity of ManitobaHealth Sciences Centre
Fundersnot available
KeywordsBiologyPhylogenetic treePopulationGenomeViral evolutionGeneticsPandemicVirologySequence analysisPhylogeneticsVirusCoronavirusEvolutionary biologyGeneCoronavirus disease 2019 (COVID-19)DiseaseMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

COVID-19 has greatly affected public health and world economy. In this study, we analyzed 129 full-length genomes of SARS-CoV-2 viruses of a Canadian population during early phase of the pandemic. Phylogenetic analysis revealed three major paths of transmission of SARS-CoV-2 viruses into Canada. Twenty-one substitutions that have frequencies greater than 3% of viral population were identified. Analysis of these substitutions indicated that P1427I (ORF1b), Y1464C (ORF1b), and Q57H (ORF3a) might affect functions of the corresponding SARS-CoV-2 encoded proteins. Additionally, we found the evidence of positive selection on the ORF3a and codon 614 of Spike protein, suggesting the viral components responsible for host entry and activation of inflammation response were targeted by host immune responses. The study showed genomic variation and evolution of SARS-CoV-2 in a Canadian population. These information may help develop preventive strategies and be used for further study of SARS-CoV-2 pathogenesis and therapeutics development.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.080
GPT teacher head0.299
Teacher spread0.219 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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