Validity of the 4-compartment model using dual energy X-ray absorptiometry-derived body volume in overweight individuals
Bibliographic record
Abstract
The purpose of the present study was to assess the validity of dual-energy X-ray absorptiometry (DXA) to estimate body volume (BV) for use in a 4-compartment (4C) body composition model in an overweight/obese population. Body composition of 61 overweight/obese adults (age: 37.3 ± 10.0 years; height: 170.2 ± 9.5 cm; body mass: 97.1 ± 17.4 kg) was measured by 2 methods: a criterion 4C model and a DXA-derived BV 4C model. For both models, bioelectrical impedance spectroscopy was used to estimate total body water; total body bone mineral content was measured by a full-body DXA scan. For the criterion 4C model, BV was derived from air displacement plethysmography; for the DXA-4C model, BV was derived from previously published coefficients. Total error (TE) and standard error of the estimate (SEE) values for BV (TE = 1.11 L; SEE = 0.01 L) and body fat percentage (%fat) (TE = 2.92%; SEE = 0.32%) represented good to very good agreement between models. The DXA-derived measures of body composition (BV: 96.6 ± 18.1 L; %fat: 39.5% ± 8.1%; fat mass: 38.5 ± 11.9 kg), were significantly greater (p < 0.001) than 4C criterion measures (BV: 95.7 ± 17.6 L; %fat: 37.0% ± 7.6%; FM: 36.0 ± 10.8 kg) with the exception of lean mass, which was significantly lower (p < 0.001; DXA-4C: 58.2 ± 11.2 kg; criterion 4C: 60.7 ± 12.0 kg). Although small statistically significant mean differences were observed, TE and SEE results support the use of the DXA-4C method, which requires less time and equipment, for valid estimates of body composition in overweight/obese individuals.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".