The Obesity Epidemic
Bibliographic record
Abstract
The prevalence of obesity is increasing at an alarming rate and with it the occurrence of a number of comorbidities, including cardiovascular disease, type 2 diabetes, stroke, and certain types of cancer. Approximately one third of adults in the US population are currently classified as obese. Globally, >400 × 106 adults are classified as obese, a number that is expected to double by 2015. Consequently, obesity and its associated health problems are placing a large burden on an already overwhelmed healthcare system. The worldwide costs attributable to this disease are estimated to be between 0.7% and 2.8% of total healthcare expenditures. Furthermore, medical costs for obese individuals are substantially higher than for nonobese people. Obesity is a multifactorial disease caused by a chronic energy surplus in which energy intake exceeds energy expenditure, leading to the accumulation of excess adipose tissue. Regulation of energy homeostasis is a complex process, and that fact imparts a considerable challenge in trying to elucidate the pathogenesis of obesity. Although poor lifestyle choices, including inappropriate diets and lack of physical activity, undoubtedly play a large role, genetic susceptibility also puts an individual at increased risk. The majority of obesity therapies have been aimed at behavior modification and pharmacologic intervention, although to date these therapies have led to only modest weight loss. Although less common, bariatric surgery has led to substantial long-term weight loss in morbidly obese patients; this type of treatment, however, is both invasive and costly. Given the growing trend of obesity in both developed and developing countries, considerable importance has been placed on increasing awareness of the problem. In this article, 4 leaders in the field of obesity provide their opinions on obesity and discuss the latest advancements in pathogenesis, therapy, prevention, and the use of novel biomarkers to identify those at risk …
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".