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Record W4212823914 · doi:10.14745/ccdr.v48i01a03f

L’expérience au Yukon avec la COVID-19 : restrictions de voyage, variants et propagation entre les non vaccinés

2022· article· fr· W4212823914 on OpenAlexaffvenueabout
Sara McPhee-Knowles, Bryn Hoffman, Lisa Kanary

Bibliographic record

VenueRelevé des maladies transmissibles au Canada · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsQueen's UniversityYukon University
Fundersnot available
KeywordsHumanitiesCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Political science2019-20 coronavirus outbreakArtMedicineVirologyOutbreak

Abstract

fetched live from OpenAlex

L’expérience du Yukon concernant la maladie à coronavirus 2019 (COVID-19) a été intéressante; le territoire a mis en place avec succès des restrictions de voyage pour limiter l’importation du virus et a déployé les vaccins rapidement par rapport à la plupart des administrations canadiennes. Cependant, la première vague de COVID-19 du Yukon en juin et juillet 2021 a fait déborder le système de santé en raison de la transmission généralisée parmi les enfants non-vaccinés, les jeunes et les adultes, malgré une forte participation à la vaccination et le port du masque obligatoire. Cette expérience met en lumière l’importance du soutien continu aux programmes de vaccination publique, de l’adoption généralisée de vaccins dans les populations pédiatriques, et l’assouplissement judicieux des interventions non pharmaceutiques dans toutes les administrations canadiennes à mesure qu’elles rouvrent alors que des variants plus contagieux apparaissent

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)0.003
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 score0.216
Threshold uncertainty score0.434

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.003
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.002
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 head0.017
GPT teacher head0.264
Teacher spread0.247 · 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
Published2022
Admission routes3
Has abstractyes

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