Reduced Eccentric Loading of the Knee with the Pose Running Method
Bibliographic record
Abstract
PURPOSE: The aim of this study was to compare the biomechanical changes during natural heel-toe running with learned midfoot and Pose running. METHODS: Twenty heel-toe runners were instructed in midfoot running and a novel running style in which the acromium, greater trochanter, and lateral malleolus are aligned in stance (Pose running). Clinical gait analysis was performed for each running style and the biomechanical variables compared. RESULTS: In comparison with midfoot and heel-toe running Pose running was characterized by shorter stride lengths and smaller vertical oscillations of the sacrum and left heel marker. Compared with midfoot and Pose running heel-toe running was characterized by greater magnitudes and loading rates of the vertical impact force. In preparation for initial contact, the knee flexed more in Pose than in heel-toe and midfoot running. The ankle at initial contact was neutral in Pose compared with a dorsiflexed and plantarflexed position in heel-toe and midfoot running, respectively. The knee power absorption and eccentric work were significant lower (P < 0.05) in Pose than in either heel-toe or midfoot running. In contrast, there was a higher power absorption and eccentric work at the ankle in Pose compared with heel-toe and midfoot running. CONCLUSIONS: Pose running was associated with shorter stride lengths, smaller vertical oscillations of the sacrum and left heel markers, a neutral ankle joint at initial contact, and lower eccentric work and power absorption at the knee than occurred in either midfoot or heel-toe running. The possibility that such gait differences could be associated with different types and frequencies of running injuries should be evaluated in controlled clinical trails.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.005 | 0.001 |
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".