Bibliographic record
Abstract
Sport shoes can have an influence on the energetics of human movement. The two main aspects where sport shoes can play a role are in maximizing the energy which is returned to the athlete and minimizing the energy which is lost by the athlete. Maximum values of energy storage in a shoe sole are on the order of 10 J. However, not all of this energy is returned to the athlete as shoe midsoles lose approximately 30% of the energy input. Depending on the movement, energy return sometimes occurs at the wrong time, frequency, location and in the wrong direction which compromises the ultimate influence on improving performance. As a result, the actual influence that energy return has on performance is probably minimal. Examples of the strategy to minimize energy loss include (1) reducing the mass of the shoe, (2) using appropriate midsole materials which dissipate unwanted vibrations, (3) implementing constructions which improve the stability of the ankle joint and (4) increasing the bending stiffness of shoe midsoles which reduces the energy lost at the metatarso-phalangeal joint. Energy that has not been lost for tasks not directly related to the actual performance may be applied to the movement and may result in an increase of athletic performance. We propose that athletic footwear can have a much larger influence on performance by minimizing the energy which is lost as opposed to maximizing the energy which is returned.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".