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Record W2105187259 · doi:10.1086/521119

Provision of Antiretroviral Therapy in South Africa: Unique Challenges and Remaining Obstacles

2007· review· en· W2105187259 on OpenAlexaboutno aff
Bisola O. Ojikutu, Christopher Jack, Gita Ramjee

Bibliographic record

VenueThe Journal of Infectious Diseases · 2007
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyAntiretroviral therapyEconomic growthQuarter (Canadian coin)Universal designDeveloping countryPoliticsMedicineDevelopment economicsHuman immunodeficiency virus (HIV)GeographySocioeconomicsPolitical scienceVirologySociologyViral loadEconomics

Abstract

fetched live from OpenAlex

From 2003 to 2006, the number of human immunodeficiency virus-infected people in sub-Saharan Africa able to access antiretroviral therapy (ART) has increased from 100,000 to >1 million. The World Health Organization estimates that >3.5 million patients are still in need. The challenges to more expeditious provision of ART in Africa are many. This article is an analysis of the barriers to ART scale-up that are unique to South Africa. With 5.3 million people infected and 1 million needing ART, this country carries nearly one-quarter of the treatment burden of the continent. Although South Africa is undeniably a middle-income nation, inequities born of apartheid, lack of political commitment, poverty, and cultural barriers have significantly slowed efforts to provide universal access to ART to South African citizens.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.090
GPT teacher head0.385
Teacher spread0.294 · 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 designNot applicable
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

Citations33
Published2007
Admission routes1
Has abstractyes

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