← Back to cohort
Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis
Benjamin F. Voight, Laura J. Scott, Valgerður Steinthórsdóttir, Andrew P. Morris, Christian Dina, Ryan Welch, Eleftheria Zeggini, Cornelia Huth, Yurii S. Aulchenko, Guðmar Þorleifsson, Laura McCulloch, Teresa Ferreira, Harald Grallert, Najaf Amin, Guanming Wu, Cristen J. Willer, Soumya Raychaudhuri, Steve McCarroll, Claudia Langenberg, Oliver Hofmann, Josée Dupuis, Lu Qi, Ayellet V. Segrè, Mandy van Hoek, Pau Navarro, Kristin Ardlie, Beverley Balkau, Rafn Benediktsson, Amanda J. Bennett, Roza Blagieva, Eric Boerwinkle, Lori L. Bonnycastle, Kristina Bengtsson Boström, Bert Bravenboer, Suzannah Bumpstead, Noisël P Burtt, G. Charpentier, Peter S. Chines, Marilyn C. Cornelis, David Couper, Gabe Crawford, Alex S. F. Doney, Katherine S. Elliott, Amanda L. Elliott, Michael R. Erdos, Caroline S. Fox, Christopher S. Franklin, Martha Ganser, Christian Gieger, Niels Grarup, Todd J. Green, Simon J. Griffin, Christopher J. Groves, Candace Guiducci, Samy Hadjadj, Neelam Hassanali, Christian Herder, Bo Isomaa, Anne Jackson, Paul R V Johnson, Torben Jørgensen, Wen H. Kao, Norman Klopp, Augustine Kong, Peter Kraft, Johanna Kuusisto, Torsten Lauritzen, Man Li, Aloysius G. Lieverse, Cecilia M. Lindgren, Valeriya Lyssenko, Michel Marre, Thomas Meitinger, Kristian Midthjell, Mario A. Morken, Narisu Narisu, Peter M. Nilsson, Katharine R. Owen, Felicity Payne, John R. B. Perry, Ann-Kristin Petersen, Carl G. P. Platou, Christine Proença, Inga Prokopenko, Wolfgang Rathmann, Nigel W. Rayner, Neil R. Robertson, Ghislain Rocheleau, Michael Roden, Michael Sampson, Richa Saxena, Beverley M. Shields, Peter Shrader, Gunnar Sigurðsson, Thomas Sparsø, Klaus Straßburger, Heather M. Stringham, Qi Sun, Amy J. Swift, Barbara Thorand, Jean Tichet, Rob M. van Dam, Timon W. van Haeften, Thijs van Herpt, Jana V. van Vliet‐Ostaptchouk, G. Bragi Walters, Michael N. Weedon, Cisca Wijmenga, Jacqueline C.M. Witteman, Richard N. Bergman, Stéphane Cauchi, Francis S. Collins, Anna L. Gloyn, Ulf Gyllensten, Torben Hansen, G. A. Hitman, Albert Hofman, David J. Hunter, Kristian Hveem, Markku Laakso, Karen L. Mohlke, Andrew D. Morris, Peter P. Pramstaller, Igor Rudan, Eric J.G. Sijbrands, Lincoln Stein, Jaakko Tuomilehto, André G. Uitterlinden, Mark Walker, Nicholas J. Wareham, Richard M. Watanabe, Gonçalo R. Abecasis, Bernhard O. Boehm, Harry Campbell, Mark J. Daly, Andrew T. Hattersley, Frank B. Hu, James B. Meigs, James S. Pankow, Oluf Pedersen, H‐Erich Wichmann, Inês Barroso, José C. Florez, Timothy M. Frayling, Leif Groop, Robert Sladek, Unnur Þorsteinsdóttir, James F. Wilson, Thomas Illig, Philippe Froguel, Cornelia M. van Duijn, Kāri Stefánsson, David Altshuler, Michael Boehnke, Mark I. McCarthy
Bibliographic record
VenueNature Genetics · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityMcGill University and Génome Québec Innovation CentreOntario Institute for Cancer Research
FundersNational Center for Research ResourcesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Human Genome Research InstituteNational Institutes of HealthNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institute for Health and Care ResearchNational Institute on Drug AbuseWellcome Trust
KeywordsBiologyGenome-wide association studyLocus (genetics)GeneticsType 2 diabetesGenetic associationGene1000 Genomes ProjectSingle-nucleotide polymorphismDiabetes mellitusGenotypeEndocrinology
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 machine prediction
Teacher imitationNot 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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 head0.006
GPT teacher head0.276
Teacher spread0.270 · 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 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
Citations1,797
Published2010
Admission routes1
Has abstractno