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Record W4394061375 · doi:10.1016/s0140-6736(24)00469-0

Semaglutide versus placebo in people with obesity-related heart failure with preserved ejection fraction: a pooled analysis of the STEP-HFpEF and STEP-HFpEF DM randomised trials

2024· article· en· W4394061375 on OpenAlexafffund
Javed Butler, Sanjiv J. Shah, Mark C. Petrie, Barry A. Borlaug, Steen Z. Abildstrøm, Melanie J. Davies, G. Kees Hovingh, Dalane W. Kitzman, Daniél Vega Møller, Subodh Verma, Mette Nygaard Einfeldt, Marie L.S. Lindegaard, Søren Rasmussen, Walter P. Abhayaratna, Fozia Ahmed, Tuvia Ben‐Gal, Vijay Chopra, Justin A. Ezekowitz, Michael Fu, Hiroshi Ito, Małgorzata Lelonek, Vojtěch Melenovský, Béla Merkely, Julio Núñez, Eduardo Perna, Morten Schou, Michele Senni, Kavita Sharma, Peter van der Meer, Dirk von Lewinski, Dennis Wolf, Mikhail Kosiborod

Bibliographic record

VenueThe Lancet · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsCanadian VIGOUR CentreUniversity of TorontoUniversity of AlbertaSt. Michael's Hospital
FundersAmerican RegentGedeon RichterHLS TherapeuticsGilead SciencesServierDeutsche ForschungsgemeinschaftNovo NordiskDaiichi-SankyoNational Institutes of HealthRegeneron PharmaceuticalsDexcomBritish Heart FoundationCytokineticsAstraZenecaAmarin CorporationNational Heart, Lung, and Blood InstituteSun PharmaBoston Scientific CorporationBristol-Myers SquibbU.S. Department of DefenseEli Lilly and CompanyNational Institute on AgingCSL BehringSanofiAmgenPfizerAlnylam Pharmaceuticals
KeywordsHeart failure with preserved ejection fractionMedicineCardiologyInternal medicineSemaglutidePlaceboHeart failureEjection fractionType 2 diabetesDiabetes mellitusEndocrinologyAlternative medicine

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0110.015
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.020
GPT teacher head0.273
Teacher spread0.253 · 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 designMeta-analysis
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

Citations323
Published2024
Admission routes2
Has abstractno

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