MétaCan
Menu
← Back to cohort
Record W4210321193 · doi:10.1093/cid/ciac115

Genital Immune Cell Activation and Tenofovir Gel Efficacy: A Case-Control Study

2022· article· en· W4210321193 on OpenAlexafffund
Lenine J. P. Liebenberg, Jo Ann S Passmore, Farzana Osman, Janine Jewanraj, Andile Mtshali, J. Gerardo García‐Lerma, Walid Heneine, Angela Holder, Derseree Archary, Sinaye Ngcapu, Aida Sivro, Leila E. Mansoor, Quarraisha Abdool Karim, Salim S. Abdool Karim, Lyle R. McKinnon

Bibliographic record

VenueClinical Infectious Diseases · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Manitoba
FundersEuropean and Developing Countries Clinical Trials PartnershipCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesAfrican Academy of SciencesRoyal SocietyDepartment of Science and Technology, Republic of South AfricaTides FoundationU.S. President’s Emergency Plan for AIDS ReliefUnited States Agency for International Development
KeywordsMedicineImmune systemTenofovirImmunologyIntracellularHuman immunodeficiency virus (HIV)Pre-exposure prophylaxisDeoxyadenosineImmunityVirologyInternal medicineBiologyMen who have sex with menAdenosine

Abstract

fetched live from OpenAlex

Genital inflammation (GI) undermines topical human immunodeficiency virus (HIV) pre-exposure prophylaxis (PrEP) efficacy through unknown mechanisms. Here, associations between activated endocervical CD4 + T-cell numbers and higher deoxyadenosine triphosphate (dATP) concentrations suggest that competition for intracellular metabolites within HIV target cells may reduce the efficacy of antiretroviral-based PrEP in women with GI.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.031
GPT teacher head0.379
Teacher spread0.348 · 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

Labeled directly by 2 models reading the full record.

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

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueClinical Infectious Diseases→Same topicHIV/AIDS Research and Interventions→French-language works237,207→