Segment Kinematics Differ Between Jump and Drop Landings Regardless of Practice
Bibliographic record
Abstract
Joint kinematics differ between jump and drop landings and there is evidence that segment kinematics may also be different. The purpose of this research was to compare lower extremity segment kinematics for jump and drop landings, and to examine if multiple days of practice would influence these kinematics. Men (n = 9) and women (n = 15) performed 4 sessions of jump and drop landings (40 cm and 60 cm) in a motion-capture laboratory. Segment kinematics at initial contact, foot flat, and peak knee flexion were compared between landing types and across visits. At initial contact, foot plantar flexion was greater in jump versus drop landings (P < .05). At initial contact and foot flat, forward leg inclination and pelvis flexion were greater in jump landing (P < .05), while thigh flexion was greater in drop landings (P > .05). The differences in leg and thigh angles at initial contact and foot flat altered lower extremity posture. These results are in contrast to a previous study; this suggests that drop landing can be modified to have the same mechanics as jump landing. As practice did not influence drop landing mechanics (P > .05), specific control strategies and instructions need to be identified.
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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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".