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Record W1931777665 · doi:10.1002/jmv.23893

Epidemiology of GB virus type C among patients infected with HIV in Singapore

2014· article· en· W1931777665 on OpenAlexaff
Chun Kiat Lee, Julian W. Tang, Lily Chiu, Tze Ping Loh, Dariusz P. Olszyna, Nicholas Chew, Sophia Archuleta, Evelyn Siew-Chuan Koay

Bibliographic record

VenueJournal of Medical Virology · 2014
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Alberta HospitalAlberta Hospital EdmontonUniversity of Alberta
Fundersnot available
KeywordsEpidemiologyVirologyGenotypeMedicineHuman immunodeficiency virus (HIV)GB virus CVirusViral diseaseMolecular epidemiologySidaFlaviviridaeBiologyImmunologyInternal medicineGeneticsGene

Abstract

fetched live from OpenAlex

Several studies have shown that individuals co-infected with GB virus type C (GBV-C), and human immunodeficiency virus (HIV) have slower progression to acquired immunodeficiency syndrome (AIDS) and a prolonged lifespan, compared to those infected with only HIV. In Singapore, despite the steadily increasing number of HIV infections in recent years, there are no studies documenting the extent of GBV-C/HIV co-infection in this group of patients. To fill this dearth of information, two GBV-C screening assays was performed on 80 archived HIV-1-positive samples from the National University Hospital. The overall prevalence of GBV-C co-infection among patients infected with HIV in this study was 10% (8/80). Phylogenetic analysis of the eight dual-infection cases revealed that genotypes 3 (4/8, 50%) and 2a (2/8, 25%) were the main genotypes circulating among these Singaporean HIV patients. One case each of genotypes 2b (1/8, 12.5%) and 4 (1/8, 12.5%), which have not been described previously in Singapore, were identified. These findings hint at the complex epidemiology of GBV-C in different patient groups and a larger study would be needed to characterize, and understand the potential clinical impact of GBV-C co-infection on the patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.356
Teacher spread0.322 · 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 teacher head, not a consensus.

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

Citations11
Published2014
Admission routes1
Has abstractyes

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