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Record W2097795823

HIV prevention for rural youth in Nigeria: background overview.

2012· article· en· W2097795823 on OpenAlexfundaboutno aff
Andrew G Onokerhoraye, Eleanor Maticka‐Tyndale

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsHuman immunodeficiency virus (HIV)MedicineGeneral partnershipRural areaDeveloping countryEconomic growthSocioeconomicsEnvironmental healthPolitical scienceFamily medicineSociology
DOInot available

Abstract

fetched live from OpenAlex

The negative impact of the HIV/AIDS epidemic has been a major challenge to sub-Saharan Africa. Although the rate of new HIV infections in sub-continent has decreased, the total number of people living with HIV continues to rise. Most of the people infected with HIV/AIDS in sub-Saharan Africa are within the age bracket of 15 to 35 years. It has been estimated that about 80% of the infected group are aged 20-29 years. It is against the background of the challenges posed by HIV/AIDS to young people that the Canadian-Nigerian partnership Action Research on HIV Prevention for Rural Youth was conceived. This paper provides the background to the outcomes reported in this special edition of this journal by reviewing the HIV/AIDS situation in sub-Saharan Africa and the nature of the associated response; discussing the rationale for the Action Research which focuses on Nigeria; and outlining the key components of the research.

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)0.002
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.277
GPT teacher head0.446
Teacher spread0.169 · 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

Citations20
Published2012
Admission routes2
Has abstractyes

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