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Record W2889289468 · doi:10.14745/ccdr.v40is3a05

Canada’s Vaccine Vigilance Working Group

2014· article· en· W2889289468 on OpenAlexafffundvenueabout
N Ahmadipour, Ellen L. Toth, BJ Law

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldMedicine
TopicIntramuscular injections and effects
Canadian institutionsPublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsPharmacovigilanceVigilance (psychology)ImmunizationMedicinePublic healthPublic relationsWorking groupBusinessEnvironmental healthPolitical scienceAdverse effectPsychologyImmunologyNursingPharmacology

Abstract

fetched live from OpenAlex

The Vaccine Vigilance Working Group (VVWG) was created in 2004 as part of the National Immunization Strategy to strengthen vaccine safety in Canada. The Group has representation from all federal/provincial/territorial immunization programs across the country, as well as Health Canada regulators and the Immunization Monitoring Program ACTive (IMPACT) network. VVWG works to harmonize vaccine safety monitoring and adverse event reporting and management across Canada by developing and following national guidelines and seeking out best pharmacovigilance practices, including training. It also provides a national vaccine safety sentinel network that uses several mechanisms to rapidly share information on emerging safety issues to enable effective public health response. The "vigilance" in VVWG emphasizes the watchful, ever alert nature and activities of the Group's work. Increased public and health professional awareness of the VVWG's role and activities should help to allay concerns about vaccine safety that lead to vaccine hesitancy and in turn limit the effectiveness of immunization.

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)0.008
metaresearch head score (Gemma)0.017
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: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.001
Scholarly communication0.0040.001
Open science0.0040.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0130.004

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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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
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

Citations2
Published2014
Admission routes4
Has abstractyes

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