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Record W2744780366 · doi:10.1093/infdis/jix393

Age-Related Differences in Influenza B Infection by Lineage in a Community-Based Sentinel System, 2010–2011 to 2015–2016, Canada

2017· article· en· W2744780366 on OpenAlexafffundabout
Danuta M. Skowronski, Catharine Chambers, Gaston De Serres, Suzana Sabaiduc, Anne‐Luise Winter, James A. Dickinson, Jonathan B. Gubbay, Kevin Fonseca, Steven J. Drews, Hugues Charest, Christine Martineau, Mel Krajden, Martin Petric, Nathalie Bastien, Yan Li

Bibliographic record

VenueThe Journal of Infectious Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of CanadaProvincial Laboratory of Public HealthUniversity of TorontoUniversity of CalgaryUniversity of AlbertaUniversité LavalInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecPublic Health OntarioBC Centre for Disease ControlUniversity of British Columbia
FundersCanadian Institutes of Health ResearchPfizer
KeywordsLineage (genetic)VirologyMedicineBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Age-related differences in influenza B lineage detection were explored in the community-based Canadian Sentinel Practitioner Surveillance Network (SPSN) from 2010-2011 to 2015-2016. Whereas >80% of B(Victoria) cases were <40 years old, B(Yamagata) cases showed a bimodal age distribution with 27% who were <20 years old and 61% who were 30-64 years old, but with a notable gap in cases between 20 and 29 years old (4%). Overall, the median age was 20 years lower for B(Victoria) vs B(Yamagata) cases (20 vs 40 years; P < .01). Additional phylodynamic and immuno-epidemiological research is needed to understand age-related variation in influenza B risk by lineage, with potential implications for prevention and control across the lifespan.

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)0.003
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 score0.017
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.048
GPT teacher head0.341
Teacher spread0.293 · 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

Citations38
Published2017
Admission routes3
Has abstractyes

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