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Record W2975208726 · doi:10.1093/cid/ciz936

Viral Blips After Treatment Initiation During Acute Human Immunodeficiency Virus Infection

2019· article· en· W2975208726 on OpenAlexaff
Trevor A. Crowell, Suteeraporn Pinyakorn, Carlo Sacdalan, Eugène Kroon, Donn Colby, Suwanna Puttamaswin, Sasiwimol Ubolyam, Rapee Trichavaroj, Oratai Butterworth, Esra Abacı Türk, Corinne McCullough, Nicolas Chomont, Mark de Souza, Merlin L. Robb, Nittaya Phanuphak, Jintanat Ananworanich

Bibliographic record

VenueClinical Infectious Diseases · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersEMD SeronoChulalongkorn UniversityViiV HealthcareU.S. Department of DefenseGilead SciencesHenry M. Jackson FoundationNational Institutes of HealthU.S. Department of Health and Human ServicesMerck
KeywordsVirologyViral loadHuman immunodeficiency virus (HIV)Viral infectionImmunologyVirusMedicine

Abstract

fetched live from OpenAlex

Transient viral blips ≥20 copies/mL were observed in 16.9% of acutely treated adults with HIV. Blip incidence increased from 0.0 (95% CI, 0.0-2.9)/100 person-years after ART in Fiebig I to 15.9 (7.6-29.2) in Fiebig V. Increasing viral load and Fiebig stage at ART initiation were independently predictive of blips.

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)0.005
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
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 head0.022
GPT teacher head0.345
Teacher spread0.323 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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