Association between abdominal adipose tissue mass with anthropometric and cardiometabolic variables in a subgroup of males and females from the Canola Oil Multicentre Intervention Trial (COMIT)
Bibliographic record
Abstract
Subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) differ metabolically. Excessive VAT is linked to obesity‐related disease. We evaluated the association between baseline abdominal SAT, VAT and cardiometabolic (glucose) and anthropometric measurements in a subgroup of participants from COMIT (F=7, M=7) with increased waist circumference (F: >;80 cm; M: >; 94 cm). MRI images were analyzed to separate the SAT and VAT; 3 slices centered between lumbar vertebrae L4–5 were calculated. Abdominal and total fat mass were measured by DXA. In females, SAT was positively correlated with abdominal (r=0.86, p=0.013) and total (r=0.82, p=0.02) fat mass and with waist circumference (r=0.84, p=0.02). In males, VAT was positively associated with abdominal fat mass (r=0.93, p=0.002) and demonstrated a strong tendency with waist circumference (r=0.75, p=0.051). SAT also correlated with total fat mass (r=0.73, p=0.06). Glucose levels were positively associated with SAT and VAT in females (r=0.84, p=0.02; r=0.86, p=0.04). In summary, in females, SAT is positively correlated with fat mass, waist circumference; SAT and VAT may contribute to elevated glucose levels. In males, VAT alone was positively associated with abdominal fat mass and increased waist circumference. Gender differences were observed for SAT and VAT depots; further research on differing metabolic responses between males and females is warranted. Grant Funding Source : Canola Council of Canada
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".