A Comparison of Cardinal Gaze Speed between Major League Baseball Players, Amateur Prospects, and Non-athletes
Bibliographic record
Abstract
PurposeSensorimotor variables have been shown to predict performance in professional baseball players. However, cardinal gaze speed in baseball players has received only limited attention. This study tested the hypothesis that the cardinal gaze speed in Major League Baseball (MLB) players would be faster than in amateur prospects and non-athletes. MethodSeventeen MLB athletes, 160 amateur prospects, and 128 non-athletes were tested using an eye-tracking test (i.e., the RightEye CGP test) designed to measure cardinal gaze speed. ResultsMLB players had significantly faster cardinal gaze speed than either amateur prospects or non-athletes. Moreover, there were significant differences in cardinal gaze speed across different directions. ConclusionsThis was the first study to examine the speed of gaze in the cardinal positions in an athletic context. The results highlight the significant difference in cardinal gaze speed between MLB players, amateur prospects, and non-athletes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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; 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".