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Record W2037046278 · doi:10.1038/ng.446

Twenty bone-mineral-density loci identified by large-scale meta-analysis of genome-wide association studies

2009· review· en· W2037046278 on OpenAlexafffund
Karol Estrada, M. Carola Zillikens, Fernando Rivadeneira, Najaf Amin, Unnur Styrkársdóttir, Unnur Þorsteinsdóttir, Kari Stefansson, Gudmar Thorleifsson, Augustine Kong, David Karasik, Yi‐Hsiang Hsu, Douglas P. Kiel, Nicole Soranzo, J. Brent Richards, Tomi Pastinen, Timothy D. Spector, Frances M. K. Williams, Scott G. Wilson, John P. A. Ioannidis, Fotini K. Kavvoura, Yanhua Zhou, Serkalem Demissie, L. Adrienne Cupples, Ben A. Oostra, Stuart H. Ralston

Bibliographic record

VenueNature Genetics · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill University and Génome Québec Innovation CentreMcGill University
FundersNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institute of Arthritis and Musculoskeletal and Skin DiseasesVersus ArthritisEuropean CommissionZonMwCanadian Institutes of Health ResearchCentre for Medical Systems BiologyNational Institute for Health and Care ResearchErasmus Medisch CentrumWellcome TrustNederlandse Organisatie voor Wetenschappelijk OnderzoekMinisterie van Onderwijs, Cultuur en Wetenschap
KeywordsGenome-wide association studyBiologySingle-nucleotide polymorphismBone mineralOsteoporosisGeneticsQuantitative trait locusGenetic associationSNPComputational biologyGeneEndocrinologyGenotype

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.348
Teacher spread0.309 · 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 designMeta-analysis
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

Citations706
Published2009
Admission routes2
Has abstractno

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