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Record W2005198297 · doi:10.1097/qad.0b013e3283303e04

Persistent HIV RNA shedding in semen despite effective antiretroviral therapy

2009· article· en· W2005198297 on OpenAlexaff
Prameet M. Sheth, Colin Kovacs, Kimdar Sherefa Kemal, R. Brad Jones, Janet Raboud, Richard Pilon, Charles la Porte, Mario Ostrowski, Mona Loutfy, Harold Burger, Barbara Weiser, Rupert Kaul

Bibliographic record

VenueAIDS · 2009
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of OttawaPublic Health Agency of CanadaUniversity of TorontoUniversity Health NetworkOttawa HospitalHealth CanadaWomen's College HospitalMaple Leaf Medical ClinicPublic Health Ontario
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Health and Medical Research CouncilamfAR, The Foundation for AIDS ResearchMedical Research CouncilNational Institutes of HealthEtablissement Français du Sang
KeywordsSemenSexual transmissionSex organViral loadViral sheddingHuman immunodeficiency virus (HIV)Antiretroviral therapyLentivirusRegimenVirologyMedicineImmunologyTransmission (telecommunications)BiologyViral diseaseInternal medicineAndrologyVirusMicrobicide

Abstract

fetched live from OpenAlex

Effective antiretroviral therapy (ART) may reduce HIV sexual transmission by lowering genital HIV levels. A prospective study of men starting ART (n = 25) demonstrated rapid, substantial reductions in semen HIV RNA. However, despite an undetectable blood viral load, isolated semen HIV shedding was detected at more than one visit in 12 of 25 (48%) participants, with semen HIV RNA levels exceeding 5000 copies/ml in four of 25 (16%). Isolates were drug-sensitive, and this phenomenon was not associated with semen drug levels or regimen.

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)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.326
Teacher spread0.308 · 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

Citations132
Published2009
Admission routes1
Has abstractyes

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