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Record W3135127507 · doi:10.1097/qad.0000000000002865

Kidney injury biomarkers during exposure to tenofovir-based preexposure prophylaxis

2021· article· en· W3135127507 on OpenAlexaff
Thomas L. Nickolas, Jonathan Barasch, Kenneth K. Mugwanya, Andrea D. Branch, Renee Heffron, Valentine Wanga, Nelly Mugo, Allan Ronald, Connie Celum, Deborah Donnell, Jared M. Baeten, Christina Wyatt

Bibliographic record

VenueAIDS · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of Manitoba
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious Diseases
KeywordsEmtricitabineMedicinePre-exposure prophylaxisRenal functionTenofovirPlaceboRandomized controlled trialIncidence (geometry)Internal medicineProteinuriaKidney diseaseKidneyUrologyHuman immunodeficiency virus (HIV)Antiretroviral therapyImmunologyPathologyViral loadMen who have sex with men

Abstract

fetched live from OpenAlex

We previously reported a higher incidence of non-albumin proteinuria and a small but significant decline in estimated glomerular filtration rate (eGFR) among HIV-negative adults randomized to emtricitabine/tenofovir disoproxil fumarate preexposure prophylaxis (FTC/TDF PrEP) versus placebo. In a nested case--control study among participants randomized to FTC/TDF PrEP, established kidney injury biomarkers measured at 12 months were not significantly different between participants who subsequently experienced one of these kidney endpoints and randomly selected controls who did not.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.297
Teacher spread0.284 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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