Tempo hry v tenise na French Open 2017
Bibliographic record
Abstract
Title: Tempo of tennis play at French Open 2017 Objectives: Goal of this thesis is to find out, what is the tempo of men's tennis play at French Open 2017, compare individual tempos at individual sets after first and second service and also compare tempo of tennis play during 1st and 2nd round to quarter and semifinal matches. Methods: Basic method of this work is indirect observation. From available video records of 10 tennis plays at French Open 2017 tournament we measured length of the rally, number of hits, length of the break and tempo of the play. Notation analysis was performed based on data gathered from this observation. Results: Average tempo of play is 1,34 seconds. Average rally length is 7,18 seconds and average number of hits for rally is 5,36. Time required to start another rally is 22,2 seconds. After second service, number of hits increase dramatically and break time between rallys is increased. Keywords: Tennis, French Open 2017, tempo of tennis play, time, rally, clay
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".