Bibliographic record
Abstract
Evaluation of: Parikh RM, Joshi SR, Pandia K. Index of central obesity is better than waist circumference in defining metabolic syndrome. Metab. Syndr. Relat. Disord. 7(6), 525–527 (2009).The metabolic syndrome, a constellation of anthropometric and metabolic abnormalities, has been studied extensively in the last decade, as well as its associated increased risk of cardiovascular diseases. Various definitions and criteria have been used to diagnose the metabolic syndrome. One proposed parameter is waist circumference cut-offs according to gender and ethnicity. A novel parameter called the index of central obesity (ICO) was suggested. It takes into account the height and the waist circumference of the subjects. The article under evaluation studies the usefulness of ICO over waist circumference alone in the International Diabetes Federation definition of the metabolic syndrome in comparison with the National Cholesterol Education Program Adult Treatment Panel III definition. The results showed that the modified International Diabetes Federation definition of the metabolic syndrome incorporating ICO as a parameter of central obesity appears to improve sensitivity but reduce specificity. The modified definition identified the presence of the metabolic syndrome in shorter subjects with a waist circumference smaller than the suggested cut-offs.
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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.016 | 0.033 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".