A methodological proof-of-concept of the teeter-totter effect
Bibliographic record
Abstract
The Nike Vaporfly 4% (VP4) shoe is popular due to its unique design and reported performance benefits. However, the underlying mechanisms responsible for the improvements remain unclear. One proposed mechanism is the teeter-totter effect. This study aimed to 1) experimentally test the teeter-totter theory by estimating the teeter-totter moment (MTT) in the VP4 compared to a flat shoe (CONTROL) and 2) quantify the change in the anterior-posterior position of the centre of pressure (Δxa-p) in the VP4 compared to the CONTROL. Plantar pressures and high-speed video were recorded from 15 runners in two shoe conditions. The VP4 generated a larger propulsion moment, MP, (∫MPdt = 90.46 ± 38.87 Nms; p < 0.001, d = 1.95), suggesting the presence of an MTT in the VP4 (∫MTTdt = 57.16 ± 24.35 Nms) when compared to the CONTROL (∫MPdt = 33.30 ± 14.52 Nms). Δxa-p was greater in the VP4 (Δxa-p = 9.48 ± 6.08 mm; p < 0.001, d = 2.07) compared to the CONTROL (Δxa-p = 0.54 ± 0.67 mm). This study provides a methodological proof-of-concept for the teeter-totter theory. The findings highlight the possibility of a teeter-totter effect resulting in greater heel propulsion while running in an AFT shoe construction, assuming a constant muscle moment and pivot point.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".