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Record W2097632414 · doi:10.1086/377002

Cytomegalovirus (CMV) Glycoprotein B Genotypes and Response to Antiviral Therapy, in Solid‐Organ–Transplant Recipients with CMV Disease

2003· article· en· W2097632414 on OpenAlexaff
Atul Humar, Deepali Kumar, Christian Gilbert, Guy Boivin

Bibliographic record

VenueThe Journal of Infectious Diseases · 2003
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversité LavalCentre hospitalier universitaire de QuébecToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsGenotypeGanciclovirCytomegalovirusBetaherpesvirinaeViral loadVirologyHuman cytomegalovirusImmunologyDiseaseBiologyHerpesviridaeViral diseaseMedicineVirusInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

Cytomegalovirus (CMV) can be classified into 4 glycoprotein B (gB) genotypes, on the basis of sequence variation in the UL55 gene. We assessed the effect that CMV gB genotype has on virologic and clinical response to therapy, in 50 solid-organ-transplant recipients with CMV disease. CMV loads were determined at regular intervals after the start of therapy. Genotype results were correlated with CMV-load kinetics in response to therapy with ganciclovir. At the onset of treatment, the distribution of CMV gB genotypes was as follows: gB1, 19/50 (38%); gB2, 9/50 (18%); gB3, 12/50 (24%); gB4, 2/50 (4%); and mixed-genotype infection, 8/50 (16%). Between viral genotype groups, time to clearance of CMV, failure to clear CMV, and calculated CMV-load half-life after the start of therapy were not significantly different. The CMV gB genotype did not affect the rate of disease recurrence or occurrence of tissue-invasive disease. It appears that the gB genotype, which causes CMV disease, does not significantly influence CMV-load kinetics or clinical response to therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.123
Threshold uncertainty score0.604

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.286
Teacher spread0.272 · 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.

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

Citations80
Published2003
Admission routes1
Has abstractyes

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