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Record W3213283278 · doi:10.1080/00325481.2021.2002616

Managing the gastrointestinal side effects of GLP-1 receptor agonists in obesity: recommendations for clinical practice

2021· article· en· W3213283278 on OpenAlex
Sean Wharton, Melanie J. Davies, Dror Dicker, Ildiko Lingvay, Ofri Mosenzon, Domenica Rubino, Sue D. Pedersen

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.

Bibliographic record

VenuePostgraduate Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsLMC Diabetes & Endocrinology (Canada)McMaster UniversityYork University
Fundersnot available
KeywordsMedicineAdverse effectClinical PracticeType 2 diabetesOverweightGlucagon-like peptide-1ObesityManagement of obesitySide effect (computer science)Intensive care medicineWeight lossDiabetes mellitusInternal medicineFamily medicineEndocrinology

Abstract

fetched live from OpenAlex

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are well established in clinical practice for the treatment of type 2 diabetes, and are approved and recommended for weight management in overweight or obesity. Gastrointestinal side effects are well known as the most common adverse effects of these agents and represent a potential barrier for use, particularly at higher doses. Drawing on both published evidence and our collective clinical experience, we aim to guide practitioners through managing these side effects with a view to optimizing therapeutic outcomes with GLP-1RAs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.806
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.054
GPT teacher head0.383
Teacher spread0.329 · 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