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Record W2412682202 · doi:10.2807/ese.17.04.20066-en

Cross-reactive antibody to swine influenza A(H3N2) subtype virus in children and adults before and after immunisation with 2010/11 trivalent inactivated influenza vaccine in Canada, August to November 2010

2012· article· en· W2412682202 on OpenAlexafffundabout
Danuta M. Skowronski, Gaston De Serres, Naveed Z. Janjua, Jennifer L. Gardy, Vladimir Gîlca, Marc Dionne, Marie‐Ève Hamelin, Chantal Rhéaume, Guy Boivin

Bibliographic record

VenueEurosurveillance · 2012
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversité LavalInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecBC Centre for Disease ControlUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCPublic Health AgencyPublic Health Agency of Canada
KeywordsVirologyMedicineAntibodyVirusInfluenza vaccineInfluenza A virusVaccinationImmunology

Abstract

fetched live from OpenAlex

In pre- and post-immunisation sera from children (17-120 months-old) and adults (20-59 years-old) immunised with 2010/11 trivalent inactivated influenza vaccine, we assessed age-related patterns of sero-susceptibility and vaccine-induced cross-reactive antibodies to a representative swine H3N2 (swH3N2) and a related ancestral human H3N2 (A/Sydney/5/1997) influenza virus. Few children but a greater proportion of adults showed pre-immunisation haemagglutination inhibition titres ≥40 to either virus. Titres increased with age among children but decreased in adults. Fewer than 20% showed a four-fold rise in antibody titres to either virus following immunisation. Further investigation is warranted to guide ongoing risk assessment and response to emerging swine H3N2 viruses.

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)0.001
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 score0.293
Threshold uncertainty score0.589

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.315
Teacher spread0.297 · 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

Citations35
Published2012
Admission routes3
Has abstractyes

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