An Analysis of a Strategic Decision in the Sport of Curling
Why this work is in the frame
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Bibliographic record
Abstract
We apply decision analysis to an important decision in the sport of curling. In particular, we examine the choice between taking a single point or blanking an end in the latter stages of a curling game. There are benefits and drawbacks associated with each alternative. Taking a single point provides the team with an additional point but transfers the last-shot advantage to the opposition. Blanking an end foregoes an additional point but retains the last-shot advantage. Based on the observation of world-class competitions, North American curlers will always attempt to blank an end, while their European counterparts have been known to opt for the single point. We develop a decision tree to conceptualize the choices. Then, we use data from over 900 national championship curling games to empirically determine the expected values of each alternative. Our results indicate that blanking the end is the better alternative.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it