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Record W4409565473 · doi:10.1038/s41591-025-03645-3

Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery

2025· article· en· W4409565473 on OpenAlexafffund
J German, Mattia Cordioli, Veronica Tozzo, Sarah Urbut, Kadri Arumäe, Roelof A. J. Smit, Jiwoo Lee, Josephine H. Li, Adrian Janucik, Yi Ding, Akintunde O. Akinkuolie, Henrike Heyne, Andrea Eoli, Chadi Saad, Yasser Al‐Sarraj, Rania G. Abdel‐latif, Shaban Mohammed, Moza Al Hail, Alexandra Barry, Zhe Wang, Tatiana Cajuso, Andrea Corbetta, Pradeep Natarajan, Samuli Ripatti, Anthony Philippakis, Łukasz Szczerbiński, Bogdan Paşaniuc, Zoltán Kutalik, Hamdi Mbarek, Ruth J. F. Loos, Uku Vainik, Andrea Ganna

Bibliographic record

VenueNature Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcGill University
FundersDavid Geffen School of Medicine, University of California, Los AngelesNational Institute of Diabetes and Digestive and Kidney DiseasesPerelman School of Medicine, University of PennsylvaniaNational Institutes of HealthNational Center for Advancing Translational SciencesNational Human Genome Research InstituteAgencja Badań MedycznychTartu ÜlikoolNational Institute of Mental HealthUniversité de LausanneEesti TeadusagentuurBroad InstituteMcGill UniversityAmerican Diabetes AssociationHelsingin ja Uudenmaan SairaanhoitopiiriUCLA Health SystemClinical and Translational Science Institute, University of California, Los AngelesHelsingin YliopistoUniversity of PennsylvaniaMassachusetts General Hospital
KeywordsWeight lossBody mass indexObesityMedicineWeight changeType 2 diabetesBiobankDemographyInternal medicineGerontologyDiabetes mellitusEndocrinologyBioinformaticsBiology

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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)0.000
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 score0.013
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.243
Teacher spread0.236 · 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 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

Citations34
Published2025
Admission routes2
Has abstractyes

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