Body composition measured by dual‐energy X‐ray absorptiometry half‐body scans in obese children
Bibliographic record
Abstract
AIM: To perform a methods comparison of a left or right half-body scan versus whole-body scan for measuring body composition in a sample of obese children. METHODS: A group of obese children (n = 58; ≥ 95th BMI percentile; 8-18 years) were required to undergo a dual-energy X-ray absorptiometry (DXA) body composition measurement as part of an ongoing cohort study; 34 fit within the imaging field of the DXA scanner and were eligible for inclusion in the present analysis. Percent fat, total mass, fat mass, lean mass and bone mineral content (BMC) were estimated from half-body scans and compared with the whole-body results. Assessment was completed using GE enCORE 11.40 software. RESULTS: In comparing left- and right-side scans to whole-body scans, there was significant correlation for all body composition variables (p ≤ 0.005, R(2) = 0.996-1.0). Bland Altman analyses also showed high levels of agreement between half-body estimates and whole-body measurements. CONCLUSION: This study supports using a half-body scan methodology for percent fat, total mass, fat mass, lean mass, and BMC as a valid alternative to full-body analysis in obese children and youth.
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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 | 0.002 | 0.005 |
| 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 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".