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Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
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
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.
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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.870
Threshold uncertainty score0.691
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 head0.321
GPT teacher head0.504
Teacher spread0.183 · 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 itQuick stats
Citations201
Published2023
Admission routes2
Has abstractno