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Record W4413780770 · doi:10.14745/ccdr.v51i08a05f

Surveillance de la sécurité du vaccin Imvamune lors de l'éclosion de mpox de 2022 au Canada

2025· article· fr· W4413780770 on OpenAlexvenueaboutno aff
Charlotte Wells, Yuhui Xu, Ashley Weeks, Amanda Shaw, Susanna Ogunnaike-Cooke

Bibliographic record

VenueRelevé des maladies transmissibles au Canada · 2025
Typearticle
Languagefr
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Contexte : Au Canada, en 2020, l'indication de l'utilisation d'Imvamune a été élargie pour inclure l'immunisation contre la variole, la mpox et les infections et maladies liées à l'orthopoxvirus chez les adultes âgés de 18 ans et plus et considérés comme présentant un risque élevé d'exposition.Méthodes : Depuis l'introduction de cette nouvelle utilisation du vaccin et tout au long des éclosions de mpox en 2022, l'Agence de la santé publique du Canada (l'Agence) a surveillé de près la sécurité du vaccin Imvamune par l'intermédiaire du Système canadien de surveillance des effets secondaires suivant l'immunisation (SCSESSI).Résultats : Cet article décrit les rapports d'événements indésirables suivant l'immunisation (ÉISI) étant survenus après l'administration d'Imvamune, et ayant été soumis à la base de données du SCSESSI entre le 24 mai 2022 et le 11 décembre 2022, lors de l'activation de l'intervention d'urgence du Canada.Conclusion : La surveillance des rapports d'ÉISI suivant l'immunisation par Imvamune soumis au SCSESSI n'a pas identifié d'enjeux de sécurité vaccinale nouveaux ou inattendus dans la population adulte canadienne.L'Agence de la santé publique du Canada continue de surveiller les signaux potentiels de sécurité vaccinale.

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)0.004
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 score0.984
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.226
Teacher spread0.220 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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