A new footwear technology to promote non-heelstrike landing and enhance running performance: Fact or fad?
Bibliographic record
Abstract
This study sought to compare the kinetics and kinematics data in a group of habitual shod runners when running in traditional running shoes and newly designed minimalist shoes with lug platform. This novel footwear design claims to simulate barefoot running and reduce energy loss during impact. We compared footstrike angle (FSA), vertical average (VALR) and instantaneous (VILR) loading rates, energy loss and initial vertical stiffness between two shoe conditions. Runners demonstrated a decreased FSA while running in minimalist shoes with lug platform than traditional shoes (P = 0.003; Cohen's d = 0.918). However, we did not observe a landing pattern transition. VALR and VILR between two footwear conditions showed no significant difference (P = 0.191-0.258; Cohen's d = 0.304-0.460). Initial vertical stiffness (P = 0.032; Cohen's d = 0.671) and energy loss (P = 0.044; Cohen's d = 0.578) were greater when running in minimalist shoes with lug platform. The results show that minimalist shoes with lug platform reduce the FSA but may not lead to a landing pattern switch or lower vertical loading rates. Interestingly, the new shoe design leads to a greater energy loss than traditional running shoes, which could be explained by a higher initial vertical stiffness.
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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 | 0.001 |
| 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 | 0.001 |
| 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".