Appraisal of the impact of Bariatric surgery on health related quality of life and work productivity in morbidly obese patients
Bibliographic record
Abstract
Background: In the last decades, morbid obesity has emerged as an increasingly prevalent chronic metabolic disorder affecting populations located in both developed and emerging countries.This condition leads to major public health issues and is associated with significant medical, quality of life and economic burdens.Obesity therefore represents a major health epidemic challenge facing health care professionals and governments over the next decades.Obesity may be associated to many different causes, its cornerstone being weight gain due to a lack of positive energy balance.A reliable approach to determine if a person has an excessive amount of adipose tissue is to calculate the ratio of their weight in kilogram divided by their height in meters square.This weight-for-height ratio is referred to as the body mass index (BMI).Many serious health conditions have been reported to be concomitant to this condition, including coronary heart disease, hypertension, stroke, type 2 diabetes, musculoskeletal disorders and cancer.Obesity is associated with increased morbidity, disability and premature mortality.Obesity is actually projected to rapidly become the leading cause of preventable death in Canada and the United States second only to tobacco abuse related deaths.According to 2013 data from Statistics Canada, approximately one in five adults age 18 and older meet the criteria for obesity, based on self-reported body mass index.Information provided by the public health agency of Canada estimate the yearly economic burden of obesity to be on the rise reaching as high as $7.1
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".