Effect of grip-enhancing agents on sliding friction between a fingertip and a baseball
Bibliographic record
Abstract
Abstract Friction between a pitcher’s fingers and the leather surface of a baseball is a key factor that influences ball delivery, causing Major League Baseball in the United States to recently enhance enforcement of rules banning the unauthorized use of friction-enhancing agents or sticky substances. Here, we examine how the application of rosin powder and sticky substances alters the friction coefficient between a fingertip and the leather of a baseball. We find that sticky substances increase friction which can positively affect ball spin rate, while rosin has the advantage of keeping friction consistent within and between individuals. Additionally, we find that baseballs used by the Nippon Professional Baseball Organization in Japan are less slippery compared with the ones used in Major League Baseball, suggesting that grip-enhancers may have a larger impact on friction for baseballs used in the United States compared to Japan. Furthermore, our results indicate that changing the characteristics of the leather the baseball is made from may increase friction, reducing the unauthorized use of sticky substances.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".