Validation of assessments to accurately analyze the body composition of highly trained sitting volleyball players: A pilot study
Bibliographic record
Abstract
Body composition is a fundamental component of physical fitness related to the performance of Sitting volleyball (SV) players. Also, establishing the best method for evaluating the body composition of these para-athletes would be highly necessary for this field. The purpose of this study was (1) to describe the body composition of male and female highly trained SV players, (2) to compare the values obtained from this population by two different methods and (3) to establish validity on one of these methods. Thirteen Brazilian SV national team players (five males and eight females) participated in this study. The air-displacement plethysmography (ADP) method as the criterion assessment and the skinfolds (SF) method were conducted for each player. Results showed that there were no significant differences between the values of all players, which ADP and SF measured for body fat percentage (BF%) and body density (BD) (p > 0.05). We found significantly different values between male and female players for BF% by SF (p = 0.04) and BD by SF (p = 0.04). A high degree of reliability was found between ADP and SF measures for BF% and BD. There were statistically significant positive correlations between BF% and BD in all values for both methods (p < 0.01). This pilot study suggests that considering the magnitude of space, expense, and other limitations related to the ADP method against the SF method, we recommend using the SF method, which is a valid, viable and reliable method for measuring body composition in elite SV players.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".