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Record W4283587189 · doi:10.3390/pathogens11070724

Point-of-Care Tests for HIV Drug Resistance Monitoring: Advances and Potentials

2022· article· en· W4283587189 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePathogens · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsPoint-of-care testingHIV drug resistanceHuman immunodeficiency virus (HIV)MedicineDrug resistanceAntiretroviral therapyTurnaround timeRegimenIntensive care medicineViral loadVirologyComputer scienceImmunologySurgeryBiologyMicrobiology

Abstract

fetched live from OpenAlex

HIV/AIDS is a global public health crisis that is yet to be contained. Effective management of HIV drug resistance (HIVDR) supported by close resistance monitoring is essential in achieving the WHO 95-95-95 targets, aiming to end the AIDS epidemic by 2030. Point-of-care tests (POCT) enable decentralized HIVDR testing with a short turnaround time and minimal instrumental requirement, allowing timely initiation of effective antiretroviral therapy (ART) and regimen adjustment as needed. HIVDR POCT is of particular significance in an era when ART access is scaling up at a global level and enhanced HIVDR monitoring is urgently needed, especially for low-to-middle-income countries. This article provides an overview of the currently available technologies that have been applied or potentially used in HIVDR POCT. It may also benefit the continued research and development efforts toward more innovative HIVDR diagnostics.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.014
GPT teacher head0.279
Teacher spread0.265 · 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