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Record W2258666009 · doi:10.1136/bmj.h6468

PrEP on demand cuts HIV transmission in high risk men, study finds

2015· letter· en· W2258666009 on OpenAlexaboutno aff
Michael McCarthy

Bibliographic record

VenueBMJ · 2015
Typeletter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSerodiscordantMen who have sex with menPre-exposure prophylaxisMedicineHuman immunodeficiency virus (HIV)PlaceboRegimenRandomized controlled trialTransmission (telecommunications)Intervention (counseling)DemographyFamily medicineGynecologyAlternative medicineInternal medicineViral loadPsychiatryAntiretroviral therapy

Abstract

fetched live from OpenAlex

Pre-exposure prophylaxis (PrEP) taken by men when they have sex with other men reduced the risk of transmission of HIV-1 by 86%, a new randomized, placebo controlled trial published in the New England Journal of Medicine has found.1 Previous trials have shown that PrEP taken daily can reduce HIV-1 transmission among men who have sex with men, heterosexual men and women, intravenous drug users, and serodiscordant couples. However, adherence remains a challenge. The hypothesis of the new study, conducted in France and Canada, was that PrEP taken on demand instead of part of a once a day regimen would achieve greater adherence and thus greater efficacy. In the trial, called the Intervention Preventive de l’Expostion aux Risque avec et pour les Gays (IPERGAY) trial, 400 men who had tested negative for HIV and who engaged in unprotected anal sex with men were randomized to take either …

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0190.002

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 head0.040
GPT teacher head0.371
Teacher spread0.331 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2015
Admission routes1
Has abstractyes

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