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Record W1933553852 · doi:10.1080/21645515.2015.1009816

Acceptability of live attenuated influenza vaccine by vaccine providers in Quebec, Canada

2015· article· en· W1933553852 on OpenAlexaffabout
Ève Dubé, Dominique Gagnon, Marilou Kiely, Nicole Boulianne, Monique Landry

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2015
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsMinistère de la Santé et des Services Sociaux (Québec)Université LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsLive attenuated influenza vaccineMedicineVaccinationInfluenza vaccineSeasonal influenzaInfluenza seasonFamily medicineVirologyCoronavirus disease 2019 (COVID-19)Internal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

A live attenuated influenza vaccine (LAIV) was offered during the 2012-13 influenza season in Quebec, Canada, to children aged between 2 and 17 years with chronic medical conditions. Despite the offer, uptake of the vaccine was low. We assessed the perceptions and opinions about seasonal influenza vaccination and LAIV use among vaccine providers who participated in the 2012-13 campaign. More than 70% of them thought that LAIV was safe and effective and more than 90% considered that the vaccine was well-received by parents and healthcare professionals. According to respondents, the most frequent concerns of parents about LAIV were linked to vaccine efficacy. LAIV is well-accepted by vaccine providers involved in influenza vaccination clinics, but more information about the vaccine and the recommendations for its use are needed to increase vaccine uptake.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.034
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.072
GPT teacher head0.360
Teacher spread0.288 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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