COMPARATIVE PERFORMANCE ANALYSIS OF PGA TOUR AND ONTARIO UNIVERSITY GOLFERS
Bibliographic record
Abstract
The purposes of the study were to 1) build a model to predict scoring average for a total sample of professional (n = 82) and collegiate (n = 41) golfers using stepwise regression, 2) test the model on the samples independently using hierarchical regression, and 3); examine the significance in performance differences in the two subsamples. Both samples played two tournament rounds at the South Course of Angus Glen Golf Club; the professionals during the 2002 PGA tour Canadian Open and the collegians during the 2010 OUA championship. For the total sample, GIR percentage, putts per round, scrambling percentage and driving accuracy percentage predicted 92% of the variance in scoring average; for professionals and collegians the only the former three performance measures accounted for explained variance for scoring average (80% and 81% respectively). Professionals were significantly superior to the collegians in all four performance indices as well as scoring average.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".