Agreement between anthropometric and dual-energy X-ray absorptiometry assessments of lower-limb volumes and composition estimates in youth-club rugby athletes
Bibliographic record
Abstract
The purpose of this study was to assess the agreement of lower-limb volume estimates based on anthropometry and dual-energy X-ray absorptiometry (DXA) as a reference method in male rugby athletes. Predictive models using body mass and skinfolds were tested to improve the relative agreement between protocols (anthropometry, DXA). Rugby players (n = 41; 19.9 ± 2.2 years) volunteered for the study. Lower-limb total and fat-free volumes were estimated by anthropometry and also derived using DXA. Cross-validation between the anthropometry technique and DXA was then performed. Lower-limb volume estimates by anthropometry overestimated reference values and tended to be further from the reference values with the increase of scale. For the total sample, standard errors of measurement for volume estimates by anthropometry were 1.99 L and 1.34 L for total and fat-free volumes, respectively. Correlations with reference values were 0.81 for lower-limb volume and 0.90 for lower-limb fat-free volume. Correlations between estimated prediction equations and reference values showed higher correlations (r = 0.96 for lower-limb volume and r = 0.93 for lower-limb fat-free volume) compared with anthropometric estimates. Overall, the agreement of anthropometry method to quantify lower-limb volumes with DXA as a reference in young adult rugby players is acceptable and is a practical method when more expensive and complex techniques are not available. The consideration of body mass and lower-limb skinfolds increases the precision of lower-limb volume estimates using anthropometry in the young adult rugby players.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".