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Record W6977031681 · doi:10.60692/r2wmj-tw683

Saliva as a source of reagent to study human susceptibility to avian influenza H7N9 virus infection

2019· article· en· W6977031681 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2019
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSalivaInfluenza A virus subtype H5N1VirusHemagglutinin (influenza)Human influenzaRecombinant DNAHuman viromeInfluenza A virus

Abstract

fetched live from OpenAlex

Avian influenza H7N9 viruses are an important public health concern due to their high mortality rate and potentials for future pandemics. We investigated human susceptibility to H7N9 viruses using recombinant H7N9 hemagglutinin (HA) proteins as a probe and found a strong association between H7N9 infections and HA binding among saliva samples from 32 patients and 60 uninfected controls in Jiangsu province, China, during the 2016 epidemic season. We also found that sialyl Lex (SLex) antigen that was recognized by H7N9 HA was associated with H7N9 virus infection. Further analysis suggested that additional saccharide residues adjacent to the SLex moiety may affect the H7N9-binding specificity. Our data suggested that saliva may be a useful reagent to study human susceptibility to avian influenza H7N9 virus, which may impact the disease control and prevention of avian influenza viruses as important human pathogens.

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)0.001
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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

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 head0.093
GPT teacher head0.351
Teacher spread0.257 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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