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Record W2410421601 · doi:10.1097/inf.0000000000000816

Risk Factors for Measles in HIV-infected Children and Adolescents in Botswana

2015· article· en· W2410421601 on OpenAlexaff
Kathleen E. Wirth, Elizabeth R. Wolf, David A. Goldfarb, Ari Ho‐Foster, Michael A. Tolle, Christina L. Jacovides, Brianna Kirk, Mamiki Chise, Andrew P. Steenhoff

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsMcMaster University
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical Sciences
KeywordsMeaslesHuman immunodeficiency virus (HIV)VirologyMedicineEnvironmental healthVaccination

Abstract

fetched live from OpenAlex

We conducted a matched case-control study of 566 HIV-infected children in Botswana during a 2009-2010 measles outbreak to identify the risk factors for measles. Children in the oldest age quartile (≥13.1 years) were 4-fold more likely to acquire measles than those in the youngest quartile (<7.1 years). HIV-infected older children and adolescents may benefit from additional measles vaccination.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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