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Record W2105074464 · doi:10.1186/1471-2105-15-s7-s8

Population substructure in Cache County, Utah: the Cache County study

2014· article· en· W2105074464 on OpenAlexfundno aff
Aaron R. Sharp, Perry G. Ridge, Matthew H. Bailey, Kevin L. Boehme, Maria C. Norton, JoAnn T. Tschanz, Ronald G. Munger, Christopher Corcoran, John SK Kauwe

Bibliographic record

VenueBMC Bioinformatics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicForensic and Genetic Research
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Human Genome Research InstituteNational Institute on AgingUniversity of California, San DiegoGenentechNational Institutes of HealthNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchUniversity of California, Los AngelesServierEisaiNorthern California Institute for Research and EducationPfizerBiogenBioClinicaAlzheimer's AssociationAmorfix Life SciencesF. Hoffmann-La RocheMedpaceBristol-Myers SquibbEli Lilly and CompanyAstraZenecaNovartis Pharmaceuticals CorporationSynarcDana FoundationBayer HealthCareAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsFoundation for the National Institutes of Health
KeywordsInternational HapMap ProjectPopulationCachePopulation stratificationGeographyDemographyComputer scienceBiologyGeneticsGenotypeGenotypingSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Population stratification is a key concern for genetic association analyses. In addition, extreme homogeneity of ethnic origins of a population can make it difficult to interpret how genetic associations in that population may translate into other populations. Here we have evaluated the genetic substructure of samples from the Cache County study relative to the HapMap Reference populations and data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). RESULTS: Our findings show that the Cache County study is similar in ethnic diversity to the self-reported "Whites" in the ADNI sample and less homogenous than the HapMap CEU population. CONCLUSIONS: We conclude that the Cache County study is genetically representative of the general European American population in the USA and is an appropriate population for conducting broadly applicable genetic studies.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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