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Record W4387178755 · doi:10.3390/v15102023

Gen Z and HIV—Strategies for Optimizing the Care of the Next Generation of Adolescents Living with HIV

2023· review· en· W4387178755 on OpenAlexaff
Inès Dufour, Yves Fougère, Tessa Goetghebuer, Marc Hainaut, Benoît Mukinayi Mbiya, Fatima Kakkar, Jean Cyr Yombi, Dimitri Van der Linden

Bibliographic record

VenueViruses · 2023
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)PandemicMedicinePopulationCoronavirus disease 2019 (COVID-19)GerontologyFamily medicineEnvironmental health

Abstract

fetched live from OpenAlex

The management of adolescents living with HIV represents a particular challenge in the global response to HIV. The challenges specific to this age group include difficulties engaging and maintaining them in care, challenges with transition to adult care, and limited therapeutic options for treatment-experienced patients, all of which have been jeopardized by the COVID-19 pandemic. This paper summarizes some of the challenges in managing adolescents living with HIV, as well as some of the most recent and innovative therapeutic approaches in this population.

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 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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.721
Threshold uncertainty score0.249

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 head0.249
GPT teacher head0.413
Teacher spread0.164 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations3
Published2023
Admission routes1
Has abstractyes

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