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Record W4417524227 · doi:10.18773/austprescr.2025.052

Injectable drugs for weight management

2025· article· en· W4417524227 on OpenAlex
Natasha Yates, Terri-Lynne South

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

VenueAustralian Prescriber · 2025
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsCanadian Fitness and Lifestyle Research Institute
Fundersnot available
KeywordsIncretinWeight lossGallstonesAdverse effectObesityWeight managementGastric emptyingDiabetes mellitusType 2 diabetes

Abstract

fetched live from OpenAlex

Obesity management is complex; medications must be used in conjunction with behavioural changes and monitoring by health professionals. Injectable drugs for weight management include glucagon-like peptide-1 (GLP-1) receptor agonists (e.g. liraglutide, semaglutide) and dual glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor agonists (e.g. tirzepatide). These drugs contribute to weight loss by mimicking the incretin hormones GLP-1 and GIP to reduce appetite, change food enjoyment, slow stomach emptying and stimulate insulin release. Regaining weight is common when these drugs are stopped, so they usually need to be continued long term. Relatively minor gastrointestinal issues are common. There is also a small but real risk of more serious adverse effects, including gallstones and pancreatitis. It is important to monitor mental health, as these drugs can change a patient's relationship with food, and they may be misused by those without obesity.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.186
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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