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Record W2131152496 · doi:10.1086/655971

Cohorts for the Study of HIV‐1–Exposed but Uninfected Individuals: Benefits and Limitations

2010· review· en· W2131152496 on OpenAlexaff
Rachel Horton, Paul J. McLaren, Keith R. Fowke, Joshua Kimani, T. Blake Ball

Bibliographic record

VenueThe Journal of Infectious Diseases · 2010
Typereview
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsPublic Health Agency of CanadaUniversity of Manitoba
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)ImmunologyEnvironmental healthMedicineDemographyBiology

Abstract

fetched live from OpenAlex

Since the late 1980s, with the first identification of individuals who were exposed to human immunodeficiency virus type 1 (HIV-1) yet remained uninfected, or "HIV-1-resistant" individuals, a large number of cohorts that include HIV-exposed seronegative (HESN) subjects have been identified globally for the purpose of investigating the genetic, immunologic, and environmental factors that may help alter susceptibility to HIV-1. In this article, in light of the recent International Symposium on Natural Immunity to HIV, we review the characteristics of different groups with respect to their relative risks and briefly summarize the known cohorts that include exposed uninfected subjects worldwide.

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)0.028
metaresearch head score (Gemma)0.026
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 score0.028
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.079
GPT teacher head0.373
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

Citations83
Published2010
Admission routes1
Has abstractyes

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