Proximal-to-Distal Sequencing in Vertical Jumping With and Without Arm Swing
Bibliographic record
Abstract
Vertical jumping performance is dependent on muscle strength and motor skill. An understanding of motor skill strategies and their influence on jumping mechanics provides insight into how to improve performance. This study aimed to determine whether kinematic sequencing strategy influenced jump height, the effect of sequencing on jumping mechanics, and whether arm swing influences sequencing strategy. Women volleyball players (n = 16) performed vertical jumps with and without arm swing on force platforms while recorded with a 6-camera motion capture system. Sequencing strategy was determined as the relative time delay between pelvis and knee extension. A long time delay indicated a proximal-to-distal strategy, whereas no time delay represented a simultaneous strategy. Longer relative time delay was correlated with higher jump height in jumps with (r = 0.82, p < 0.001) and without arm swing (r = 0.58, p = 0.02). Longer relative time delay and higher jump height were associated with greater hip extensor and ankle plantar flexor net joint moments (NJM), and greater ratio of concentric to eccentric knee extensor NJM (p ≤ 0.05). Longer relative time delay and higher jump height were correlated with greater thigh and leg angular accelerations (p ≤ 0.05). These kinetic and kinematic variables, along with relative time delay and jump height were greater in jumps with arm swing than without (p ≤ 0.05), indicating arm swing promotes use of a proximal-to-distal strategy. Use of a proximal-to-distal strategy is associated with greater NJM and segment accelerations, which may contribute to better vertical jump performance.
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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 | 0.001 |
| 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".