Teeter-totter effect: a new mechanism to understand shoe-related improvements in long-distance running
Bibliographic record
Abstract
The effect of shoe mid-sole construction on running performance was discussed with reference to the Nike Vaporfly 4%.1 Drs Burns and Tam described the mid-sole thickness as the major running shoe characteristic that contributes to changes in performance. Here, we highlight the role of the curved carbon fibre plate embedded in the mid-sole, and introduce a new effect on running mechanics, the ‘ teeter-totter effect ’. During ground contact in running, the point of application of the ground reaction force moves anteriorly during the second half of ground contact towards the front end of the curved carbon fibre plate. We suggest that, in this position, the ground reaction force produces a ‘reaction’ force at the heel in upward direction (perpendicular to the direction of the plate; figure 1). Figure 1 Schematic illustration of the teeter-totter effect including the application point of the ground reaction force (red full circle) and its translation (red broken circle and line), the applied force of the runner (black arrow) at the front part of the shoe and the reaction force at the heel of the foot (red arrow) during early/mid-stance (left orientation) and push-off (right orientation). Image modified from nike.com. If the curvature of the plate is designed correctly, the teeter-totter effect …
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".