Effects of selected features of advanced footwear technology on lower limb joint work
Bibliographic record
Abstract
The objective of this study was to isolate the effects of two key components of Advanced Footwear Technology, the curved carbon fibre plate and the midsole material, on lower-limb joint work. Sixteen male recreational runners ran overground at a speed of 3.9 (±5%) metres per second in three shoe conditions: a standard Nike Vaporfly 4% (Original VP4), a modified version without the curved carbon fibre plate (No Plate) and a version with the PEBA midsole material replaced with EVA foam (EVA). Motion capture and force platform data were recorded to determine positive and negative metatarsophalangeal, ankle, knee, and hip joint work, and positive and negative foot + footwear work across the different conditions. Removing the carbon fibre plate significantly increased negative work at the metatarsophalangeal joint and positive work at the ankle. Replacing PEBA with EVA significantly reduced positive foot + footwear work. The findings of this study highlighted a group effect of the curved carbon fibre plate, which redistributed positive lower-limb joint work from the ankle to the metatarsophalangeal joint. Conversely, the results highlighted subject-specific differences in response to the midsole material, emphasising the importance of considering individual variability in footwear design elements to optimise athletic performance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".