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Record W2058346366 · doi:10.1086/315358

Clearance of Cytomegalovirus Viremia after Initiation of Highly Active Antiretroviral Therapy

2000· letter· en· W2058346366 on OpenAlexaff
Guy Boivin, Roger LeBlanc

Bibliographic record

VenueThe Journal of Infectious Diseases · 2000
Typeletter
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsMcGill UniversityUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsViremiaAntiretroviral therapyVirologyCytomegalovirusMedicineCytomegalovirus infectionsImmunologyHuman cytomegalovirusViral loadHuman immunodeficiency virus (HIV)Viral diseaseHerpesviridaeVirus

Abstract

fetched live from OpenAlex

In a recent report, O'Sullivan et al. [1] showed that immune reconstitution secondary to initiation of highly active antiretroviral therapy (HAART) in 23 human immunodeficiency virus (HIV)-infected subjects with low CD4 T cell counts (median, 35 cells/mm3) resulted in a progressive decline in cytomegalovirus (CMV) DNAemia (as measured by the Digene [Beltsville, MD] hybrid capture system) in the absence of specific anti-CMV therapy. In their study, the CMV DNA load was determined after a median of ∼1, 3, and 12 months of therapy, with a significant reduction in the CMV load noted after time point 2. To contribute to these findings, we report results of a detailed analysis of CMV viremia (conventional cell culture), antigenemia (pp65 antigen, CINApool; Biosoft, Varilhes, France), and DNAemia by means of a quantitative polymerase chain reaction (PCR) on plasma and leukocytes (Amplicor Monitor CMV test; Roche Diagnostics, Branchburg, NJ) in an antiretroviral-naive HIV-infected subject in whom HAART was initiated.

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)0.001
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0120.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.288
Teacher spread0.271 · 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 designCase report
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

Citations10
Published2000
Admission routes1
Has abstractno

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