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Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease
Wei Zhao, Asif Rasheed, Emmi Tikkanen, Jung‐Jin Lee, Adam S. Butterworth, Joanna M. M. Howson, Themistocles L. Assimes, Rajiv Chowdhury, Marju Orho‐Melander, Scott M. Damrauer, Aeron Small, Senay Asma, Minako Imamura, Toshimasa Yamauch, John C. Chambers, Peng Chen, Bishwa R. Sapkota, Nabi Shah, Sehrish Jabeen, Praveen Surendran, Yingchang Lu, Weihua Zhang, Atif Imran, Shahid Abbas, Faisal Majeed, Kevin Trindade, Nadeem Qamar, Nadeem Hayyat Mallick, Zia Yaqoob, Tahir Saghir, Syed Nadeem Hasan Rizvi, Anis Memon, Syed Zahed Rasheed, Fazal-ur-Rehman Memon, Khalid Mehmood, Naveeduddin Ahmed, Irshad Hussain Qureshi, Tanveer-us-Salam, Uzma Malik, Narinder K. Mehra, Jane Z. Kuo, Wayne Huey‐Herng Sheu, Xiuqing Guo, Chao A. Hsiung, Jyh‐Ming Jimmy Juang, Kent D. Taylor, Yi‐Jen Hung, Wen‐Jane Lee, Thomas Quertermous, I‐Te Lee, Chih‐Cheng Hsu, Erwin P. Böttinger, Sarju Ralhan, Yik Ying Teo, Tzung‐Dau Wang, Dewan S Alam, Emanuele Di Angelantonio, Steve Epstein, Sune F. Nielsen, Børge G. Nordestgaard, Anne Tybjærg‐Hansen, Robin Young, Marianne Benn, Ruth Frikke‐Schmidt, Pia R. Kamstrup, J. Wouter Jukema, Naveed Sattar, Roelof A. J. Smit, Ren‐Hua Chung, Kae‐Woei Liang, Sonia S. Anand, Dharambir K. Sanghera, Samuli Ripatti, Ruth J. F. Loos, Jaspal S. Kooner, E Shyong Tai, Jerome I. Rotter, Yii‐Der Ida Chen, Philippe Frossard, Shiro Maeda, Takashi Kadowaki, Muredach P. Reilly, Guillaume Paré, Olle Melander, Veikko Salomaa, Daniel J. Rader, John Danesh, Benjamin F. Voight, Danish Saleheen
Bibliographic record
VenueNature Genetics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesMedical Research CouncilNational Institutes of HealthNovo Nordisk FondenSydäntutkimussäätiöMinistry of Education, Culture, Sports, Science and TechnologyBritish Heart FoundationNational Center for Advancing Translational SciencesWellcome TrustNational Institute of Neurological Disorders and StrokeNational Institute for Health and Care ResearchRegeneron PharmaceuticalsFoundation for Cardiovascular ResearchNIHR Cambridge Biomedical Research CentreEuropean CommissionMcMaster UniversityFogarty International CenterNational Heart, Lung, and Blood InstitutePfizerEli Lilly and CompanyAndrea and Charles Bronfman PhilanthropiesAmerican Heart Association
KeywordsBiologyIdentification (biology)Type 2 diabetesGeneticsEtiologyDiseaseCoronary heart diseaseDiabetes mellitusHeart diseaseComputational biologyBioinformaticsInternal medicineEndocrinologyMedicine
Abstract
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 distilled prediction
Teacher imitationNot 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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.079
Threshold uncertainty score0.366
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.026
GPT teacher head0.302
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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
Citations298
Published2017
Admission routes2
Has abstractno