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Record W3025013852 · doi:10.1007/s00439-020-02177-9

Minding the gap in HIV host genetics: opportunities and challenges

2020· review· en· W3025013852 on OpenAlexaff
Shanelle N. Gingras, David Tang, Jeffrey Tuff, Paul J. McLaren

Bibliographic record

VenueHuman Genetics · 2020
Typereview
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsBiobankGenome-wide association studyBiologyHuman geneticsGeneticsGenetic associationGenomicsGenomeGenotypeSingle-nucleotide polymorphismGene

Abstract

fetched live from OpenAlex

Genome-wide association studies (GWAS) have been successful in identifying and confirming novel genetic variants that are associated with diverse HIV phenotypes. However, these studies have predominantly focused on European cohorts. HLA molecules have been consistently associated with HIV outcomes, some of which have been found to be population specific, underscoring the need for diversity in GWAS. Recently, there has been a concerted effort to address this gap that leads to health care (disease prevention, diagnosis, treatment) disparities with marginal improvement. As precision medicine becomes more utilized, non-European individuals will be more and more disadvantaged, as the genetic variants identified in genomic research based on European populations may not accurately reflect that of non-European individuals. Leveraging pre-existing, large, multiethnic cohorts, such as the UK Biobank, 23andMe, and the National Institute of Health's All of Us Research Program, can contribute in raising genomic research in non-European populations and ultimately lead to better health outcomes.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.996
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.318
GPT teacher head0.362
Teacher spread0.043 · 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 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
Published2020
Admission routes1
Has abstractyes

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