Air Displacement Plethysmography: For Fat-mass Measurement in Healthy Young Women
Bibliographic record
Abstract
PURPOSE: Dual energy X-ray absorptiometry (DXA) and air displacement plethysmography (ADP) are commonly used to assess body composition. Accurate body fat measures are valuable in a variety of populations. Because DXA, the reference standard, is expensive and labour-intensive, determining whether these two methods are interchangeable is important. METHODS: Forty-five female undergraduate students aged 21 to 33 with body mass indexes of 18.3 to 28.6 kg/m² were recruited from the University of Guelph. Each participant underwent one full-body DXA scan and one ADP assessment, to determine total percent fat mass (%FM). RESULTS: The Pearson's correlation between %FM(DXA) (27.1 ± 4.8) and %FM(ADP) (26.1 ± 5.5) indicated good association (r=0.88, p<0.01). While Bland-Altman analysis revealed no systematic bias between the two methods (R2=0.07, p=0.08), large intraindividual variation occurred (95% confidence interval: -5.86% to 4.11%); this was related to height, weight, body-surface area, and lung volume. CONCLUSIONS: The two methods were significantly correlated. Mean %FM was not significantly different and no systematic bias between methods was observed. These findings indicate that ADP and DXA may be used interchangeably for determining %FM at the group level in healthy young women; a large intraindividual variation between the methods precludes interchangeability at the individual level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".