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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
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Bibliographic record
VenueNature Genetics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Associations and Epidemiology
Canadian institutionsMcGill UniversityImpactHamilton Health SciencesUniversity of TorontoMcMaster UniversityPopulation Health Research Institute
FundersNational Heart, Lung, and Blood InstituteNational Center for Advancing Translational SciencesMedical Research CouncilGenentechNational Cancer InstituteServierShionogiNovo Nordisk FondenNovo NordiskVertex PharmaceuticalsSteno Diabetes Center CopenhagenWellcome TrustNational Institutes of HealthRegeneron PharmaceuticalsRespicardiaHarvard UniversityU.S. Department of Health and Human ServicesKowa CompanyNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiNational Institute on AgingNational Institute for Health and Care ResearchMassachusetts General HospitalGlaxoSmithKlineGuangdong Provincial People's HospitalEli Lilly and CompanyBristol-Myers SquibbAstraZenecaAmgenPfizerSteno Diabetes Center AarhusMcMaster UniversityYale University
KeywordsBiologyType 2 diabetesTranslation (biology)GeneticsComputational biologyEvolutionary biologyType (biology)Genetic genealogyDiabetes mellitusDemographyPopulationGeneSociologyEndocrinologyEcology
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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.018
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 head0.068
GPT teacher head0.359
Teacher spread0.290 · 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
GenreReview
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
Citations739
Published2022
Admission routes2
Has abstractno