The influence of midsole thickness on running turns
Bibliographic record
Abstract
Running race courses typically feature numerous turns, an element of a race typically neglected. If a thick midsole were to decrease frontal plane ankle stability, it could potentially lead to a misalignment of lower limb joints, thereby affecting turn running and overall race performance. Therefore, the purpose of this study was to determine the influence of midsole thickness on turn running performance and peak frontal plane ankle angle. Thirteen recreational athletes participated in this study, which examined the effects of two footwear conditions: one with a 35-mm thick midsole and the other with a 50-mm thick midsole. Participants performed ten running trials around each of three turns of radii 3, 6 and 9 m. No significant differences were found between footwear conditions with respect to time to completion (p = 0.028), centre of mass velocity (p = 0.179) or frontal plane ankle angle (p = 0.935) across any of the three turns. These findings would suggest footwear manufactures need not consider the impact of midsole thickness on turn running performance when designing advanced footwear technology (AFT) and consumers need not avoid a substantial stack height when purchasing running shoes.
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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 | 0.001 | 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".