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Record W4401550758 · doi:10.1111/jvh.13995

Mixed‐Genotype <scp>HCV</scp> Direct Acting Antiviral Outcomes: A <scp>CANUHC</scp> Analysis

2024· article· en· W4401550758 on OpenAlexafffundabout
Haris Imsirovic, Gisela Macphail, Brian E. Conway, Chris Fraser, Sergio Borgia, Daniel Smyth, Alexander Wong, Marie‐Louise C. Vachon, Duncan Webster, Hongqun Liu, Jordan J. Feld, Sam Lee, Curtis Cooper

Bibliographic record

VenueJournal of Viral Hepatitis · 2024
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of OttawaUniversity of TorontoDalhousie UniversityMcMaster UniversityOttawa HospitalVancouver Infectious Diseases CentreUniversité LavalUniversity of SaskatchewanWilliam Osler Health SystemUniversity of VictoriaUniversity of Calgary
FundersPublic Health AgencyPublic Health Agency of CanadaGilead Sciences
KeywordsGenotypeHepatitis C virusMedicineCohortHepatitis CVirologyHepacivirusAntiviral therapyInternal medicineImmunologyVirusChronic hepatitisBiologyGeneGenetics

Abstract

fetched live from OpenAlex

The prevalence of mixed hepatitis C virus (HCV) genotype infection in a representative Canadian HCV cohort is reported and virological response with direct acting antiviral (DAA) treatment was evaluated. 3272 HCV-positive participants were enrolled, of which 2945 (90.0%) initiated DAA therapy. 0.8% were identified with mixed genotype infection. Overall sustained virological response (SVR) was 99.1% and did not differ based on mixed genotype status. Any historical disadvantage to achieving cure with HCV treatment in mixed genotype infection has been overcome by current DAA regimens.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.587
Threshold uncertainty score0.830

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
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)0.0050.000

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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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
Published2024
Admission routes3
Has abstractyes

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