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HIV Risk in Relation to Marriage in Areas With High Prevalence of HIV Infection

2003· article· en· W2083686448 on OpenAlexaboutno aff
Judith R. Glynn, Michel Caraël, Anne Buvé, Rosemary Musonda, Maina Kahindo

Bibliographic record

VenueJAIDS Journal of Acquired Immune Deficiency Syndromes · 2003
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSpouseConcordanceDemographyTransmission (telecommunications)Human immunodeficiency virus (HIV)MedicineIncidence (geometry)Quarter (Canadian coin)Cross-sectional studyImmunologyGeographyInternal medicine

Abstract

fetched live from OpenAlex

In sub-Saharan Africa, the prevalence of HIV infection among young women is much higher than that among young men. Many women enter marriage HIV-infected, suggesting that men may be predominantly infected by their wives. Using data from cross-sectional surveys in Kisumu, Kenya, and Ndola, Zambia, in 1997, the prevalence of HIV infection at marriage was estimated from age at marriage and age- and sex-specific prevalence of HIV infection among unmarried individuals. Using a deterministic model, this prevalence was compared with measured concordance of HIV infection among recently married couples to estimate transmission probabilities within marriage and extramarital incidence of HIV infection. Over a wide range of assumptions, we estimated that at least one quarter of cases of HIV infection in recently married men were acquired from extramarital partnerships, and for both men and women, less than one half of cases of HIV infection were acquired from their spouse. In these sites, many infections in married men, even in those with HIV-infected wives, may be acquired from outside the marriage.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
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 head0.013
GPT teacher head0.282
Teacher spread0.269 · 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 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

Citations65
Published2003
Admission routes1
Has abstractyes

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