Understanding the Determinants of Weight-Related Quality of Life among Bariatric Surgery Candidates
Bibliographic record
Abstract
Obesity and its relation to quality of life are multifaceted. The purpose of this paper was to contribute evidence to support a framework for understanding the impact of obesity on quality of life in 42 morbidly obese subjects considering a wide number of potential determinants. A model of weight-related quality of life (WRQL) was developed based on the Wilson-Cleary model, considering subjects' weight characteristics, arterial oxygen pressure (PaO(2)), walking capacity (6-minute walk test, 6MWT), health-related quality of life (HRQL; Physical and Mental Component Summaries of the SF-36 PCS/MCS), and WRQL. The model of WRQL was tested with linear regressions and a path analysis, which showed that as PaO(2) at rest increased 6MWT increased. 6MWT was positively associated with the PCS, which in turn was positively related to WRQL along with the MCS. The model showed good fit and explained 38% of the variance in WRQL.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".