Bibliographic record
Abstract
The aim of this study was to investigate whether the time of an attacking action influenced the success rate of ippon (valid point) in international, elite level kendo. Selected videos of elite kendo competitors were viewed using Kinovea where the time of the attacking action could be analysed frame by frame. Movements were measured from the start of the forward or downward movement of the shinai until impact or until the point of the shinai had passed through the target area if the cut was a complete miss. There were 7.6% of attacks of 0.09s-0.12s and 6.5% of attacks of 0.13s-0.15s that led to ippon. This was a greater success rate than shorter or longer attacks. The timings of attacks performed by competitors who reached the quarter finals of tournaments were significantly faster (p < 0.001) and significantly more consistent (p = 0.006) than those performed by competitors eliminated prior to the quarter finals. These results suggest there is an optimal timing range in kendo that produces a winning strike. Mechanisms are needed to evaluate performance indicators where there are optimal values maximise the chance of success.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.003 | 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".