Validity and reliability of a new method for measuring putting stroke kinematics using the TOMI® system
Bibliographic record
Abstract
The purpose of this study was to determine the validity and reliability of a new method for measuring three-dimensional (3D) putting stroke kinematics using the TOMI device. A putting robot and a high-speed camera were used to simultaneously collect data for the validity evaluation. The TOMI device, when used in conjunction with standard 3D coordinate data processing techniques, was found to be a valid and reliable method for measuring face angle, stroke path, putter speed, and impact spot at the moment of ball contact. The validity of the TOMI(R) measurement system was quantified using the 95% limits of agreement method for each aforementioned variable. The practical significance of each validity score was assessed by incorporating the maximum estimated measurement error into the stroke of the putting robot for 10 consecutive putts. All putts were executed from a distance of 4 m on a straight and flat synthetic putting surface. Since all putts were holed successfully, the measurement error for each variable was deemed to be negligible for the purposes of measuring putting stroke kinematics. The influence of key kinematic errors, at impact, on the outcome of a putt was also determined.
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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 | 0.021 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".