Softer and more resilient running shoe cushioning properties enhance running economy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Several studies have investigated whether shoe cushioning properties have an effect on running economy. However, the findings have not been unanimous. Studies have shown both increases and decreases in running economy with soft shoes, while other studies have shown participant specific differences. Therefore, the purpose of this study was to add to the body of knowledge describing the effects of shoe cushioning properties on running economy.Methods: This study was comprised of two experiments; one using a stationary metabolic analysis system to measure oxygen consumption during treadmill running, and one using a portable metabolic analysis system to measure oxygen consumption during over-ground running. Twelve aerobically fit athletes participated in each experiment. Two professionally constructed pairs of prototype running shoes were provided by adidas AG for this experiment (Soft shoe and Control shoe). The shoes were identical in construction with the only differences being the midsole material and corresponding stiffness and energy return.Results: For both the treadmill and over-ground experiments, the Soft shoe condition was associated with statistically significantly decreased oxygen consumption compared to the Control shoe condition (Treadmill p = 0.044, Over-ground p = 0.028). In the treadmill experiment, 10 of the 12 subjects consumed less oxygen while wearing the more compliant/resilient condition, with an average decrease for all subjects of 1.0%. In the over-ground experiment 9 of the 12 subjects consumed less oxygen while running in the more compliant/resilient condition, with an average decrease for all subjects of 1.2%.Conclusion: Running shoes with softer and more resilient midsoles were found to influence running economy by 1.0% on average during treadmill and over-ground experiments.
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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 | 0.000 | 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 | 0.000 |
| 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 it