MétaCan
Menu
Back to cohort
Record W4387328184 · doi:10.1038/s41591-023-02502-5

Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

2023· review· en· W4387328184 on OpenAlexafffund
Deirdre K. Tobias, Jordi Merino, Abrar Ahmad, Catherine Aiken, Jamie L. Benham, Dhanasekaran Bodhini, Amy L. Clark, Kevin Colclough, Rosa Corcoy, Sara J. Cromer, Daisy Duan, Jamie L. Felton, Ellen C. Francis, Pieter Gillard, Véronique Gingras, Romy Gaillard, Eram Haider, Alice E. Hughes, Jennifer M. Iklé, Laura M. Jacobsen, Anna R. Kahkoska, Jarno L. T. Kettunen, Raymond J. Kreienkamp, Lee‐Ling Lim, Jonna M. E. Männistö, Robert Massey, Niamh‐Maire Mclennan, Rachel G. Miller, Mario Luca Morieri, Jasper Most, Rochelle N. Naylor, Bige Özkan, Kashyap Patel, Scott J. Pilla, Katsiaryna Prystupa, Sridharan Raghavan, Mary R. Rooney, Martin Schön, Zhila Semnani‐Azad, Magdalena Sevilla-González, Pernille Svalastoga, Wubet Worku Takele, Claudia H.T. Tam, Anne Cathrine B. Thuesen, Mustafa Tosur, Amelia S. Wallace, Caroline C. Wang, Jessie J. Wong, Jennifer M. Yamamoto, Katherine Young, Chloé Amouyal, Mette K. Andersen, Maxine P. Bonham, Mingling Chen, Feifei Cheng, Tinashe Chikowore, Sian C. Chivers, Christoffer Clemmensen, Dana Dabelea, Adem Y. Dawed, Aaron J. Deutsch, Laura T. Dickens, Linda A. DiMeglio, Monika Dudenhöffer‐Pfeifer, Carmella Evans‐Molina, María Mercè Fernández-Balsells, Hugo Fitipaldi, Stephanie L. Fitzpatrick, Stephen E. Gitelman, Mark O. Goodarzi, Jessica A. Grieger, Marta Guasch‐Ferré, Nahal Habibi, Torben Hansen, Chuiguo Huang, Arianna Harris-Kawano, Heba M. Ismail, Benjamin Hoag, Randi K. Johnson, Angus G. Jones, Robert W. Koivula, Aaron Leong, Gloria K. W. Leung, Ingrid Libman, Kai Liu, S. Alice Long, William L. Lowe, Robert W. Morton, Ayesha A. Motala, Suna Önengüt-Gümüşcü, James S. Pankow, Maleesa Pathirana, Sofia Pazmiño, Dianna Perez, John R. Petrie, Camille E. Powe, Alejandra Quinteros, Rashmi Jain, Debashree Ray, Mathias Ried‐Larsen, Zeb Saeed, Vanessa Santhakumar, Sarah Kanbour, Sudipa Sarkar, Gabriela S. F. Monaco, Denise Scholtens, Elizabeth Selvin, Wayne Huey‐Herng Sheu, Cate Speake, Maggie A. Stanislawski, Nele Steenackers, Andrea K. Steck, Norbert Stefan, Julie Støy, Rachael W. Taylor, Sok Cin Tye, Gebresilasea Gendisha Ukke, Marzhan Urazbayeva, Bart Van der Schueren, Camille Vatier, John M. Wentworth, Wesley Hannah, Sara L. White, Gechang Yu, Yingchai Zhang, Shao J. Zhou, Jacques Beltrand, Michel Polak, Ingvild Aukrust, Elisa De Franco, Sarah E. Flanagan, Kristin A. Maloney, Andrew McGovern, Janne Molnes, Mariam Nakabuye, Pål R. Njølstad, Hugo Pomares‐Millan, Michele Provenzano, Cécile Saint‐Martin, Cuilin Zhang, Yeyi Zhu, Sungyoung Auh, Russell J. de Souza, Andrea J. Fawcett, Chandra Gruber, Eskedar Getie Mekonnen, Emily Mixter, Diana Sherifali, Robert H. Eckel, John J. Nolan, Louis H. Philipson, Rebecca J. Brown, Liana K. Billings, Kristen E. Boyle, Tina Costacou, John Dennis, José C. Florez, Anna L. Gloyn, Maria F. Gomez, Peter A. Gottlieb, Siri Atma W. Greeley, Kurt Griffin, Andrew T. Hattersley, Irl B. Hirsch, Marie‐France Hivert, Korey K. Hood, Jami L. Josefson, Soo Heon Kwak, Lori M. Laffel, Siew Lim, Ruth J. F. Loos, Ronald C.W., Chantal Mathieu, Nestoras Mathioudakis, James B. Meigs, Shivani Misra, Viswanathan Mohan, Rinki Murphy, Richard A. Oram, Katharine R. Owen, Susan E. Ozanne, Ewan R. Pearson, Wei Perng, Toni I. Pollin, Rodica Pop‐Busui, Richard E. Pratley, Leanne M. Redman, María J. Redondo, Rebecca M. Reynolds, Robert K. Semple, Jennifer L. Sherr, Emily K. Sims, Arianne Sweeting, Miriam S. Udler, Kimberly K. Vesco, Tina Vilsbøll, Róbert Wágner, Stephen S. Rich, Paul W. Franks

Bibliographic record

VenueNature Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversité de MontréalPopulation Health Research InstituteUniversity of ManitobaUniversité de SherbrookeMcMaster UniversityCentre Hospitalier Universitaire Sainte-JustineImpactUniversity of Calgary
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteNIHR Imperial Biomedical Research CentreNational Health and Medical Research CouncilCenter for Duchenne Muscular Dystrophy, University of California, Los AngelesMedical Research CouncilMerck Sharp and DohmeSteno Diabetes Center AarhusNational Institutes of HealthAmerican Heart AssociationNovo Nordisk FondenPfizerDiabetesforbundetHorizon 2020 Framework ProgrammeVetenskapsrådetNational Health Research InstitutesNovo NordiskHjärt-LungfondenInnovation and Technology CommissionAustralian GovernmentNorges ForskningsrådLunds UniversitetAlbert-Ludwigs-Universität FreiburgNovo Nordisk Foundation Center for Basic Metabolic ResearchEuropean Association for the Study of DiabetesPediatric Endocrine SocietyAcademy of FinlandStiftelsen för Strategisk ForskningMinistero della SaluteLeona M. and Harry B. Helmsley Charitable TrustCroucher FoundationMoonshot Research and Development ProgramCanadian Institutes of Health ResearchDiabetes UKNational Institute for Health and Care ResearchJohn Templeton FoundationBritish Heart FoundationBoettcher FoundationDiabetes Research ConnectionSun PharmaTrond Mohn stiftelseBigfoot BiomedicalDexcomInsulet CorporationEli Lilly and CompanyImmune Tolerance NetworkMannKind CorporationDoris Duke Charitable FoundationHong Kong GovernmentWellcome TrustResearch EnglandAstraZenecaEuropean CommissionSteno Diabetes Center CopenhagenHelsingin YliopistoKU LeuvenHamilton Health SciencesU.S. Department of Veterans AffairsDaiichi Sankyo EuropeYale UniversityChinese University of Hong KongSanofiAmerican Diabetes Association
KeywordsPrecision medicineMedicineMEDLINEEvidence-based medicineIntensive care medicineCommon cause and special causeAlternative medicinePathologyPolitical scienceEngineering

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)0.025
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.134

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.005
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0100.003

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 head0.321
GPT teacher head0.504
Teacher spread0.183 · 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 designNot applicable
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

Citations201
Published2023
Admission routes2
Has abstractno

Explore more

Same venueNature MedicineSame topicDiabetes Management and ResearchFrench-language works237,207