Available datapackage for study 'Effect and Safety of Semaglutide 2.4 mg Once-weekly in Subjects With Overweight or Obesity'
Bibliographic record
Abstract
This study will look at the change in participants' body weight from the start to the end of the study. The weight loss in participants taking semaglutide (a new medicine) will be compared to the weight loss of participants taking "dummy" medicine. In addition to taking the medicine, participants will have talks with study staff about healthy food choices, how to be more physically active and what you can do to lose weight. Participants will either get semaglutide or "dummy" medicine - which treatment participants get, is decided by chance. Participants will need to take 1 injection once a week. The study medicine is injected with a thin needle in a skin fold in the stomach, thigh or upper arm. The study has two phases: A main phase and an extension phase.The main phase will last for about 1.5 years. Participants will have 15 clinic visits and 10 phone calls with the study doctor. Extension phase: Approximately 300 participants will continue in the extension phase in the following countries only: Canada, Germany, the UK and selected sites in the US and Japan. These participants will be in the study for about 2.5 years.They will not receive treatment, but will attend another 5 follow-up visits with the study doctor.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.187 | 0.066 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".