Bibliographic record
Abstract
This study was performed to see ground reaction force with different soccer studs with twelve players in Human Performance Laboratory(University of Calgary). Running speed was <TEX>$4.0{\pm}0.2m/sec$</TEX> in straight running as well as vcut running. By using four different kinds of shoes; three different pairs of soccer shoes and one pair of jogging shoes, I reached a conclusion as following. In case of right and left ground reaction force, on the assumption that the positive magnitude of power is inversion and the negative is eversion, vcut running did not occur any inversion, which in the aspect of kinetic mechanics, thought to be decelerating movement. Because when eversion happens, it arises component force of power on heading direction about 8.6 times more than in the movement of straight running. In case of front and rear ground reaction, on the assumption that the positive magnitude of power is suspension power and the negative is propulsion, vcut movement is thought to be decelerating movement in the aspect of kinetic mechanics. Because on heading direction, this movement occurs component force of power about 1.8 times more suspension and 2.2 more propulsion than in the straight running movement. In case of vertical ground reaction, on the assumption that the first peak is the magnitude of power in impact and the second peak is the magnitude of power in active, we judged that the straight running movement performed more efficiently than the vcut movement in the aspect of kinetic mechanics. On the next study, I suppose that vcut running would make up an interesting subject in the aspect of improving kinetic performance ability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".