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Record W4394876112 · doi:10.1097/qai.0000000000003422

Likelihood of Trying Long-Acting Injectable Antiretroviral Therapy Among Women With HIV in Nine Sites Across the United States

2024· letter· en· W4394876112 on OpenAlexaff
Tara McCrimmon, Lauren F. Collins, Margaret Pereyra, Corbin Platamone, Amaya Perez‐Brumer, Victoria A. Shaffer, Deanna Kerrigan, Anandi N. Sheth, Mardge H. Cohen, David B. Hanna, Catalina Ramirez, Stephen J. Gange, Aadia Rana, Bani Tamraz, Lakshmi Goparaju, Tracey E. Wilson, María L. Alcaide, Morgan M. Philbin

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2024
Typeletter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersClinical and Translational Science Institute, University of California, Los AngelesNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institute of Neurological Disorders and StrokeNational Institute of Nursing ResearchFogarty International CenterNorthwestern UniversityNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Cancer InstituteNational Institute on Alcohol Abuse and AlcoholismUniversity of California, San FranciscoNational Institutes of HealthNational Institute on Deafness and Other Communication DisordersNational Institute on Drug AbuseNational Institute on Minority Health and Health DisparitiesNational Institute of Dental and Craniofacial ResearchGeorgia Clinical and Translational Science AllianceCenter for AIDS Research, University of North Carolina at Chapel HillCenter for AIDS Research, University of Alabama at Birmingham
KeywordsAntiretroviral therapyHuman immunodeficiency virus (HIV)MedicineAntiretroviral treatmentDemographyFamily medicineViral loadSociology

Abstract

fetched live from OpenAlex

McCrimmon, Tara MPH, MIA; Collins, Lauren F. MD, MSc; Pereyra, Margaret DrPH; Platamone, Corbin MPH; Perez-Brumer, Amaya PhD, MSc; Shaffer, Victoria A. PhD; Kerrigan, Deanna PhD; Sheth, Anandi N MD, MSc; Cohen, Mardge H MD; Hanna, David B. PhD; Ramirez, Catalina MPH, CCRP; Gange, Stephen J. PhD; Rana, Aadia MD; Tamraz, Bani PharmD, PhD; Goparaju, Lakshmi PhD; Wilson, Tracey E PhD; Alcaide, Maria MD; Philbin, Morgan M. PhD Author Information

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)0.004
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 score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.306
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

Citations2
Published2024
Admission routes1
Has abstractyes

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