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Record W2010168447 · doi:10.1080/09540121.2014.986051

Inclusion of trans women in pre-exposure prophylaxis trials: a review

2014· review· en· W2010168447 on OpenAlexaff
Daniel J. Escudero, Thomas Kerr, Don Operario, M. Eugenia Socías, Omar Sued, Brandon D. L. Marshall

Bibliographic record

VenueAIDS Care · 2014
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsAIDS VancouverUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug Abuse
KeywordsObservational studyMedicineInclusion (mineral)Pre-exposure prophylaxisPopulationClinical trialFamily medicineHuman immunodeficiency virus (HIV)Internal medicinePsychologyEnvironmental healthMen who have sex with men

Abstract

fetched live from OpenAlex

Trans women are at high risk of HIV infection. We conducted a review to determine the extent to which trans women were eligible for inclusion in and enrolled into pre-exposure prophylaxis (PrEP) efficacy trials. Out of seven trials analyzing PrEP efficacy, we found that trans women comprised only 1.2% of one trial and 0.2% of total trial enrollments. Although an additional PrEP trial to determine efficacy among trans women may not be warranted, further research is needed to determine the effectiveness of PrEP in this marginalized population, through observational and feasibility studies. These studies should focus on unique barriers that trans women may experience while obtaining access to PrEP, such as gender discrimination, transphobia, and violence.

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)0.007
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.993
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.059
GPT teacher head0.430
Teacher spread0.371 · 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.

Study designSystematic review
DomainMethods
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

Citations69
Published2014
Admission routes1
Has abstractyes

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