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Record W2060592185 · doi:10.1007/s10461-011-9892-3

Preventing Human Immunodeficiency Virus Infection Among Sexual Assault Survivors in Cape Town, South Africa: An Observational Study

2011· article· en· W2060592185 on OpenAlexaff
Michelle E. Roland, Landon Myer, Lorna J. Martin, Anastasia Maw, Priya Batra, Elizabeth Arend, Thomas J. Coates, Lynette Denny

Bibliographic record

VenueAIDS and Behavior · 2011
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsColumbia College
FundersFogarty International CenterNational Institute of Allergy and Infectious DiseasesNational Institute of Mental HealthUniversity of California, San FranciscoCenter for AIDS Research, University of WashingtonNational Institutes of Health
KeywordsMedicineHealth psychologyPublic healthPsychological interventionSeroconversionHuman immunodeficiency virus (HIV)Observational studyInternal medicinePsychiatryImmunology

Abstract

fetched live from OpenAlex

We describe 131 South African sexual assault survivors offered HIV post-exposure prophylaxis (PEP). While the median days completed was 27 (IQR 27, 28), 34% stopped PEP or missed doses. Controlling for baseline symptoms, PEP was not associated with symptoms (OR = 1.30, 95% CI = 0.66, 2.64). Factors associated with unprotected sex included prior unprotected sex (OR = 6.46, 95% CI = 3.04, 13.74), time since the assault (OR = 1.33, 95% CI = 1.12, 1.57) and age (OR = 1.30, 95% CI = 1.08, 1.57). Trauma counseling was protective (OR = 0.18, 95% CI = 0.05, 0.58). Four instances of seroconversion were observed by 6 months (risk = 3.7%, 95% CI = 1.0, 9.1). Proactive follow-up is necessary to increase the likelihood of PEP completion and address the mental health and HIV risk needs of survivors. Adherence interventions and targeted risk reduction counseling should be provided to minimize HIV acquisition.

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 score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.216
GPT teacher head0.376
Teacher spread0.160 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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