Validity of judo-specific tests to assess neuromuscular performance of judo athletes
Bibliographic record
Abstract
Uchi-komi Fitness Test (UFT) is a specific judo test that evaluates physiological fitness of judo athletes in similar conditions to judo matches. Neuromuscular parameters obtained by generic and judo-specific tests would aid to get more information about its criterion validity. This study aimed to analyse the relationship between UFT and shoulder external (PTEX) and internal (PTINT) rotation torque, handgrip strength (HGS) and vertical jumps (VJs) performance. The relationship between UFT and Judogi grip strength test (JGST) was also investigated. Eighteen male judo athletes participated in this study. Athletes performed neuromuscular tests (VJ, PTEX, PTINT and HGS) and judo-specific tests (JGST and UFT). Pearson’s correlation was used with the level set at p < 0.05. Significant correlation was found between UFT and all VJ variables (r = 0.50–0.72, p < 0.004), UFT a + b (two first series of UFT) and PTEX (r = 0.49, p = 0.033), UFT and PTINT (r = 0.47, p = 0.044). Also, UFT was correlated to JGST (r = 0.50–0.72, p < 0.044, respectively). We conclude that muscle power of lower limbs, PTEX and PTINT was related to UFT. Strength-endurance in the upper limbs (JGST) was also related to the UFT performance.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".