Bibliographic record
Abstract
During sprinting, the ankle absorbs energy while flexing and performs work whileextending, with the total mechanical work done by the ankle joint surpassing that of theknee and hip joint combined.1 Ankle joint moment and angle have been observed as aclosely coupled system, and therefore validates modelling the joint as a torsion spring.2Therefore, the ankle exhibits characteristics with potential for mechanical enhancementto athletic performance. Thus, the purpose of this project was to begin a researchinitiative to improve ankle function through angular spring behaviour optimization.Previous studies have reported ankle joint stiffness characteristics, but the literatureis somewhat limited. This study began with biomechanics analysis performed onkinematic and kinetic normative data collected from the initial phases of maximaleffort sprint starts. Joint moments were calculated through inverse dynamics and jointstiffness was determined during the loading and unloading phases from linear fitsto the ankle angle moment relationship. Results showed that loading stiffness wasalways larger than unloading stiffness, with loading stiffness decreasing and unloadingstiffness increasing with the number of steps from sprint start. The second part of thisstudy initiated development of ankle apparel that modifies joint stiffness. The anklejoint can be enhanced in its spring-like behaviour through the addition of externalsprings, acting as supplemental elements in parallel with the joint musculature. Thesuccess of lower leg amputee leaf-spring prosthetics, which completely replace theankle joint, further support the use of external springs. A working prototype wasdeveloped, implementing a brace design independent of the shoe and incorporatingadjustable stiffness and resting length spring elements. Design characteristics such asweight, comfort, and ease of use were also accounted for. Future studies involvingthe ankle brace will determine what functions and levels of stiffness have beneficialimpacts on 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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".