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Record W4413655283 · doi:10.1016/j.jvacx.2025.100711

The Canadian National Vaccine Safety (CANVAS) network: Cross-sectional analysis of seasonal influenza vaccine safety in children during the 2013/2014 to 2019/2020 influenza seasons

2025· article· en· W4413655283 on OpenAlexafffundabout
Jimmy Lopez, Otto G. Vanderkooi, James D. Kellner, Louis Valiquette, Gaston De Serres, Karina A. Top, Jennifer E. Isenor, Matthew Muller, Monika Naus, Julie A. Bettinger

Bibliographic record

VenueVaccine X · 2025
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversité LavalInstitut National de Santé Publique du QuébecUniversité de SherbrookeNova Scotia Health AuthorityAlberta Children's HospitalDalhousie UniversityBC Children's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchSanofi PasteurPublic Health Agency of CanadaCoalition for Epidemic Preparedness InnovationsGlaxoSmithKline
KeywordsInfluenza vaccineEnvironmental healthSeasonal influenzaMedicineVirologyVaccine safetyVaccinationImmunizationImmunologyCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The Canadian National Vaccine Safety (CANVAS) network is a participant-centered, active surveillance system that assesses vaccine safety across Canada. Our study examined the safety profile of influenza vaccines administered to children during seven consecutive influenza seasons, from 2013/2014 to 2019/2020, to establish a baseline for health events in vaccinated and unvaccinated children before the COVID-19 pandemic. Data were collected using an online survey after a 7-day period for vaccinated and unvaccinated participants. Descriptive and inferential analyses explored the association between the influenza vaccine and health events, including associated symptoms. The proportion of health events were comparable in vaccinated and unvaccinated children. Adjusted regression models identified no statistical difference in the occurrence of health events assessed. The most frequently reported symptoms were fever, gastrointestinal symptoms (i.e., nausea/vomiting/diarrhea), and cough. Our findings observed low incidence of health events in both vaccinated and unvaccinated groups in this multi-year study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.006
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.348
Teacher spread0.328 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes3
Has abstractyes

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