Adiposity and cardiovascular disease: are we using the right definition of obesity?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Obesity is associated with a wide variety of co-morbidities, some of which may lead to disability or death.1 In general, the risk of developing co-morbidities rises as body mass index (BMI) increases. The most widely used classification of obesity is expressed in terms of BMI, where individuals whose BMI is < 18.5 kg/m2 are considered as underweight whereas those whose BMI ranges from 18.5 to 24.9 kg/m2 are classified as having normal or acceptable weight. Those whose BMI ranges from 25 to 29.9 kg/m2 are commonly referred to as overweight. Obesity is said to be present when BMI is ≥ 30 kg/m2. There are three grades of obesity: grade 1 (BMI ranging from 30 to 34.9 kg/m2), grade 2 (BMI ranging from 35.0 to 39.9 kg/m2), and grade 3 (BMI ≥ 40 kg/m2).1 There is a controversy in the literature, termed the ‘obesity paradox’, which associates better survival and fewer cardiovascular events in patients with mildly elevated BMI afflicted with chronic diseases. In a cross-sectional analysis of 95 patients with coronary artery disease (CAD), Romero-Corral et al. hypothesized that BMI will not adequately discriminate between body fatness and lean body mass.2 The investigators provided evidence that BMI does not have the discriminatory power to distinguish between lean mass and percentage body fat, especially in patients with a BMI < 30 kg/m2. As expected, BMI was correlated with both percentage body fat ( P = 0.66) and lean mass ( P = 0.41). Also, half the patients with true excess body fat, as determined by … Corresponding author. Tel: +1 418 656 4767; fax: +1 418 656 4562. E-mail address: Paul.Poirier{at}crhl.ulaval.ca
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.002 |
| 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 it