A biomechanical comparison of the vertical jump, power clean, and jump squat
Bibliographic record
Abstract
The purpose of this study was to compare the kinetics, kinematics, and muscle activation patterns of the countermovement jump, the power clean, and the jump squat with the expectation of gaining a better understanding of the mechanism of transfer from the power clean to the vertical jump. Ground reaction forces, electromyography, and joint angle data were collected from 20 trained participants while they performed the three movements. Relative to the power clean, the kinematics of the jump squat were more similar to those of the countermovement jump. The order in which the ankle, knee, and hip began extending, as well as the subsequent pattern of extension, was different between the power clean and countermovement jump. The electromyography data demonstrated significant differences in the relative timing of peak activations in all muscles, the maximum activation of the rectus femoris and biceps femoris, and in the activation/deactivation patterns of the vastus medialis and rectus femoris. The greatest rate of force development during the upward phase of these exercises was generated during the power clean (17,254 [Formula: see text]), which was significantly greater than both the countermovement jump (3836 [Formula: see text]) and jump squat (3517 [Formula: see text]) conditions (P < .001, [Formula: see text]).
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".