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Record W2619565046 · doi:10.1126/science.aai9383

Vaginal bacteria modify HIV tenofovir microbicide efficacy in African women

2017· article· en· W2619565046 on OpenAlexafffund
Ryan K. Cheu, Kenzie Birse, Alexander S. Zevin, Michelle Perner, Laura Noël‐Romas, Anneke Grobler, Garrett Westmacott, Irene Y. Xie, Jennifer Butler, Leila E. Mansoor, Lyle R. McKinnon, Jo‐Ann S. Passmore, Quarraisha Abdool Karim, Salim S. Abdool Karim, Adam Burgener

Bibliographic record

VenueScience · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
FundersCanadian Institutes of Health ResearchPublic Health AgencyDepartment of Science and Technology, Ministry of Science and Technology, IndiaUniversity of WashingtonNational Research FoundationPublic Health Agency of CanadaNational Institute of Allergy and Infectious DiseasesManitoba Health Research CouncilNational Institute of Diabetes and Digestive and Kidney DiseasesUnited States Agency for International Development
KeywordsMicrobicideBacterial vaginosisGardnerella vaginalisLactobacillusMicrobicides for sexually transmitted diseasesMicrobiologyBacteriaAnaerobic bacteriaTenofovirLactobacillus crispatusHuman immunodeficiency virus (HIV)VaginaMedicineBiologyVirologyPopulationSurgeryEnvironmental health

Abstract

fetched live from OpenAlex

and other anaerobic bacteria, which depleted tenofovir by metabolism more rapidly than target cells convert to pharmacologically active drug. This study provides evidence linking vaginal bacteria to microbicide efficacy through tenofovir depletion via bacterial metabolism.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.321
Teacher spread0.295 · 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

Citations416
Published2017
Admission routes2
Has abstractyes

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