MétaCan
Menu
Back to cohort
Record W7118172136 · doi:10.1097/qad.0000000000004351

SARS-CoV-2 breakthrough infection among people with and without HIV in Ontario, Canada

2025· article· en· W7118172136 on OpenAlexaffabout
Cassandra Freitas, C L Cooper, Abigail E. Kroch, Sarah A. Buchan, Rahim Moineddin, Gordon Arbess, Anita C. Benoit, Catharine Chambers, Muluba Habanyama, Claire E. Kendall, Jeffrey C. Kwong, Lawrence Mbuagbaw, John McCullagh, Nasheed Moqueet, Devan Nambiar, Vanessa Tran, Sharon Walmsley, Ann N. Burchell, for the CHESS Study Team

Bibliographic record

VenueAIDS · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcMaster UniversityBruyèreHIV Legal NetworkImpactWomen's College HospitalPublic Health Agency of CanadaUniversity of OttawaInstitute for Clinical Evaluative SciencesUniversity Health NetworkOttawa HospitalThe Scarborough HospitalSt. Joseph’s Healthcare HamiltonRegent Park Community Health CentrePublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)CohortCohort studyViral diseaseSidaLentivirusInfection riskImmunopathology

Abstract

fetched live from OpenAlex

We found that risk of SARS-CoV-2 breakthrough infection did not meaningfully differ between a population-based cohort of vaccinated people with HIV and a matched cohort of people without HIV after accounting for sociodemographic factors, previous SARS-CoV-2 infection, SARS-CoV-2 testing patterns and COVID-19 vaccine doses (14 December 2020 to 5 May 2024). However, rates of breakthrough infection were higher among men with HIV compared to without HIV during the pre-Omicron era.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.024
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
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 head0.017
GPT teacher head0.298
Teacher spread0.281 · 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

Explore more

Same venueAIDSSame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207