Referee report. For: Modifiable factors associated with weight regain after bariatric surgery: a scoping review [version 1; peer review: 1 approved, 1 approved with reservations]
Bibliographic record
Abstract
Background: Although bariatric surgery is the most effective treatment for severe obesity, weight regain may still occur. While non-modifiable factors associated with weight regain have been explored, modifiable factors responsible for weight regain are understudied. This scoping review aimed to identify modifiable behaviors associated with weight regain after bariatric surgery. Methods: A systematic search was conducted in Medline, Google Scholar, Cochrane, National Collaborating Centre for Methods and Tools (NCCMT) and Practice-based Evidence in Nutrition (PEN) which included articles published between January 1990 and February 2 2017, for studies examining “weight regain” after bariatric surgery. A total of 293 citations were retrieved. Eligible articles must have examined modifiable factors and addressed weight regain, or a long-term post-operative phase in which weight regain may occur. After removing duplicates, 22 studies were included for thematic analysis. Results: Key modifiable factors associated with weight regain were identified and categorized under the following themes: poor dietary adherence (e.g. excessive calorie, carbohydrate, and alcohol intake), maladaptive eating behaviors (e.g. grazing, binging), lack of on-going follow-up with the bariatric team and insufficient physical activity. Conclusions: Health professionals and self-monitoring tools for patients who have undergone bariatric surgery may benefit from these findings to direct their education and interventions to target behavior change.
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 | 0.018 | 0.318 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.014 | 0.006 |
| Insufficient payload (model declined to judge) | 0.411 | 0.130 |
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".