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Record W3035689851 · doi:10.1016/s2213-8587(20)30130-3

Risk of cardiovascular events and death associated with initiation of SGLT2 inhibitors compared with DPP-4 inhibitors: an analysis from the CVD-REAL 2 multinational cohort study

2020· article· en· W3035689851 on OpenAlexaff
Shun Kohsaka, Carolyn S.P. Lam, Dae Jung Kim, Matthew A. Cavender, Anna Norhammar, Marit E. Jørgensen, Kåre I. Birkeland, Reinhard W. Holl, Josep Franch‐Nadal, Navdeep Tangri, Jonathan E. Shaw, Jenni Ilomäki, Avraham Karasik, Su‐Yen Goh, Chern-En Chiang, Marcus Thuresson, Hungta Chen, Eric Wittbrodt, Johan Bodegård, Filip Surmont, Peter Fenici, Mikhail Kosiborod, John Wilding, Kamlesh Khunti, Hanne Løvdal Gulseth, Bendix Carstensen, Esther Bollow, Luis A. Garcı́a Rodrı́guez, Suzanne V. Arnold, Betina T. Blak, Matthias Saathoff, Yusuke Noguchi, Donna Tan, Maro R. I. Williams, Hye Won Lee, Maya Greenbloom, Oksana Kaidanovich‐Beilin, Khung Keong Yeo, Yong Mong Bee, Joan Khoo, Agnes Koong, Yee How Lau, Fei Gao, Wee Boon Tan, Hanis Abdul Kadir, Kyoung Hwa Ha, Jinhee Lee, Gabriel Chodick, Cheli Melzer Cohen, Reid Whitlock, Lucía Cea Soriano, Oscar Fernández Cantero, J Menzin, Melissa Guthrie, Dianna J. Magliano

Bibliographic record

VenueThe Lancet Diabetes & Endocrinology · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Manitoba
FundersVifor PharmaAmarin CorporationNovo NordiskSteno Diabetes Center CopenhagenSanofiDaiichi-SankyoAmgenPfizerAstraZenecaEli Lilly and CompanyGlaxoSmithKline
KeywordsMedicineCohort studyCohortMultinational corporationInternal medicinePharmacology

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 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 score0.452

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 head0.022
GPT teacher head0.254
Teacher spread0.231 · 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

Citations93
Published2020
Admission routes1
Has abstractno

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