Racial differences in visceral adipose tissue but not anthropometric markers of health-related variables
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
This study sought to determine whether visceral adipose tissue (VAT) and/or its anthropometric surrogates could significantly predict health-related variables (HRV) in overweight Caucasian (CC) (n = 36) and African-American (AA) (n = 30) women. With the use of magnetic resonance imaging, findings showed significantly higher volume and area of VAT (P < 0.0001 for both) as well as higher triacylglycerol (P = 0.009) in CC compared with AA women. Furthermore, VAT volume, race, and VAT volume x race interaction could significantly predict triacylglycerol (P = 0.0094), high-density lipoprotein cholesterol (P = 0.0057), insulin (P = 0.0002), and insulin resistance (P < 0. 0001). Additionally, the VAT volume x race interaction for insulin (P = 0.040) and insulin resistance (P = 0.003) was significant. In a separate analysis, waist circumference and race predicted the identical variables. Our results support the use of volume or area of VAT in predicting HRV in CC women; however, its use in AA women appears limited. In contrast, waist circumference can provide a suitable VAT alternative for both CC and AA women; however, VAT clearly represents the more powerful predictor.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 it