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Record W2013526400 · doi:10.1128/jcm.02601-05

Longitudinal Analysis of Genotype Distribution of Influenza A Virus from 2003 to 2005

2006· article· en· W2013526400 on OpenAlexafffund
Annie Mak, Ronak Rahmanian, Victor Lei, David S. Lawrence, Mel Krajden, Robert C. Brunham, Danuta M. Skowronski, Yan Li, Tim Booth, Swee Han Goh, Martin Petric

Bibliographic record

VenueJournal of Clinical Microbiology · 2006
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsCanadian Science Centre for Human and Animal HealthUniversity of British ColumbiaBC Centre for Disease Control
FundersMichael Smith Health Research BC
KeywordsVirologyGenotypeOrthomyxoviridaeVirusBiologyInfluenza A virusGeneticsGene

Abstract

fetched live from OpenAlex

Influenza A viruses cause yearly epidemics, in part, due to their ability to overcome immunity from previous infections through acquisition of mutations. Amino acid sequences encoded by genes 4 (HA), 6 (NA), 7 (M), and 8 (NS) from 77 H3N2 influenza A isolates, collected between November 2003 and March 2005, were analyzed to determine the extent to which the viruses mutated within epidemic periods and between the epidemics. Nucleotide and amino acid sequences were stable throughout the epidemics but experienced substantial changes between epidemics. Major changes occurred in the HA gene in 5 to 7 amino acids and the NA gene in 11 to 13 amino acids and changes of 5 amino acids occurred in the M and NS genes. In the HA gene, changes occurred in sites known to be epitopes that determine the hemagglutination inhibition reactivity, and these were shown to be associated with a change of strain from A/Fujian/411/2002-like to A/California/7/2004-like viruses. Our findings indicate that genotype determination promises to be a rapid approach for detecting new strains of influenza A viruses in a population.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.114
GPT teacher head0.458
Teacher spread0.344 · 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
Published2006
Admission routes2
Has abstractyes

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