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Record W2269609975 · doi:10.11575/prism/28046

The Descriptive Epidemiology of Influenza Vaccination and Adverse Events of Influenza Vaccination in Alberta for the 2010-2011 Vaccination Season

2013· dissertation· en· W2269609975 on OpenAlexaboutno aff
Jonathan Lambo

Bibliographic record

VenuePRISM (University of Calgary) · 2013
Typedissertation
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsVaccinationEpidemiologyMedicineVirologyEnvironmental healthAdverse effectInfluenza seasonImmunologyFamily medicineInfluenza vaccineInternal medicine

Abstract

fetched live from OpenAlex

Objective: The objective of this study was to estimate influenza vaccination coverage and describe the occurrence of adverse events related to influenza vaccination in Alberta by attributes of age, sex, geographical indicators (urban or rural), immigrants versus non-immigrants, and provider type for the 2010-2011 vaccination season. Methods: The study used aggregate data from the Alberta’s publicly funded immunization system. Denominators for influenza vaccination coverage were obtained from the health care insurance registry. Descriptive analysis included proportions to describe patterns in rates and events by attributes. Results: Variation in influenza vaccination coverage and adverse events was observed by age, sex, place of residence and in relation to being immigrant and non-immigrant. Among young children and immigrants, there were missing values of adverse events. Conclusions Influenza vaccination coverage rates for the overall population, for all age groups, and for rural and immigrant population are low. Reporting of adverse events is incomplete.

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)0.002
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 score0.135
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.053
GPT teacher head0.328
Teacher spread0.275 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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