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Record W2783484100 · doi:10.1093/pch/pxx195

Intranasal influenza vaccine: Why does Canada have different recommendations from the USA on its use?

2018· article· en· W2783484100 on OpenAlexaffabout
Theresa Tam

Bibliographic record

VenuePaediatrics & Child Health · 2018
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsLive attenuated influenza vaccineInterimMedicineAdvisory committeeImmunizationInfluenza seasonSeasonal influenzaFamily medicineOfficerInfluenza vaccineVaccinationPediatricsPolitical scienceCoronavirus disease 2019 (COVID-19)VirologyImmunologyPublic administrationDiseaseInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Canada and the USA differ in their recommendations for the use of live attenuated influenza vaccine (LAIV). The Canadian National Advisory Committee on Immunization (NACI) continues to recommend LAIV as one of the influenza vaccines available for use in children 2 to 17 years of age. The US Advisory Committee on Immunization Practices (ACIP) made an interim recommendation against the use of LAIV for the 2016 to 2017 influenza season in response to low LAIV effectiveness observed in the USA during the 2013 to 2014 to 2015 to 2016 seasons. The recommendation has been continued for the 2017 to 2018 season. In response, NACI undertook a review of available LAIV effectiveness data in children and adolescents from Canada, the USA and a number of European countries. This commentary by Canada's Chief Public Health Officer summarizes the findings of that review and provides the rationale for Canada's current continued recommendation for LAIV use.

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)0.019
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.053
Threshold uncertainty score0.385

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.005
Science and technology studies0.0070.008
Scholarly communication0.0060.003
Open science0.0050.002
Research integrity0.0130.017
Insufficient payload (model declined to judge)0.0040.001

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 head0.078
GPT teacher head0.370
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 designNot applicable
Domainnot available
GenreCommentary

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

Citations8
Published2018
Admission routes2
Has abstractyes

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