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Record W2114033673 · doi:10.1016/j.ajhg.2014.05.010

Gene-Age Interactions in Blood Pressure Regulation: A Large-Scale Investigation with the CHARGE, Global BPgen, and ICBP Consortia

2014· article· en· W2114033673 on OpenAlexaff
Jeannette Simino, Gang Shi, Joshua C. Bis, Daniel I. Chasman, Georg Ehret, Xiangjun Gu, Xiuqing Guo, Shih-Jen Hwang, Eric J.G. Sijbrands, Albert V. Smith, Germaine C. Verwoert, Jennifer L. Bragg‐Gresham, Gemma Cadby, Peng Chen, Ching‐Yu Cheng, Tanguy Corre, Rudolf A. de Boer, Anuj Goel, Toby Johnson, Chiea Chuen Khor, Behrooz Z. Alizadeh, H. Marike Boezen, Marcel Bruinenberg, Lude Franke, Pim van der Harst, Hans L. Hillege, Melanie M. van der Klauw, Johan Ormel, Dirkje S. Postma, Judith G.M. Rosmalen, Joris P. J. Slaets, Harold Snieder, Ronald P. Stolk, Bruce H. R. Wolffenbuttel, Cisca Wijmenga, Carla Lluís-Ganella, Jian’an Luan, Leo‐Pekka Lyytikäinen, Ilja M. Nolte, Xueling Sim, Siim Sõber, Peter J. van der Most, Niek Verweij, Jing Hua Zhao, Najaf Amin, Eric Boerwinkle, Claude Bouchard, Abbas Dehghan, Guðný Eiríksdóttir, Roberto Elosúa, Oscar H. Franco, Christian Gieger, Tamara B. Harris, Serge Herçberg, Albert Hofman, Andrew D. Johnson, Mika Kähönen, Kay‐Tee Khaw, Zoltán Kutalik, Martin G. Larson, Lenore J. Launer, Li Guo, Jianjun Liu, Kiang Liu, Alanna C. Morrison, Rick Twee‐Hee Ong, George Papanicolau, Brenda W.J.H. Penninx, Bruce M. Psaty, Leslie J. Raffel, Olli T. Raitakari, Kenneth Rice, Fernando Rivadeneira, Lynda M. Rose, Serena Sanna, Robert A. Scott, David S. Siscovick, André G. Uitterlinden, Dhananjay Vaidya, Ramachandran S. Vasan, Eranga N. Vithana, Uwe Völker, Henry Völzke, Hugh Watkins, Terri L. Young, Tin Aung, Murielle Bochud, Martin Farrall, Catharina A. Hartman, Maris Laan, Edward G. Lakatta, Terho Lehtimäki, Ruth J. F. Loos, Gavin Lucas, Pierre Meneton, Lyle J. Palmer, Rainer Rettig, E Shyong Tai, Yik-Ying Teo, Nicholas J. Wareham, Tien Yin Wong, Myriam Fornage, Vilmundur Guðnason, Daniel Levy, Walter Palmas, Paul M. Ridker, Jerome I. Rotter, Cornelia M. van Duijn, Jacqueline C.M. Witteman, Aravinda Chakravarti, D. C. Rao

Bibliographic record

VenueThe American Journal of Human Genetics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsLunenfeld-Tanenbaum Research InstituteOntario Institute for Cancer Research
FundersNational Center for Advancing Translational SciencesMedical Research CouncilIC Design Education CenterNational Institute for Health and Care ResearchCancer Research UKYale UniversityBiogenNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteMedtronicAmgen
KeywordsSNPGenome-wide association studySingle-nucleotide polymorphismLocus (genetics)BiologyBlood pressureGeneticsGeneEvolutionary biologyGenotypeEndocrinology

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)0.012
metaresearch head score (Gemma)0.024
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 score0.013
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.265
Teacher spread0.255 · 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

Citations149
Published2014
Admission routes1
Has abstractno

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