Comment on “Improved pivot-slide model of the motion of a curling rock”
Bibliographic record
Abstract
We point out three errors in a recent paper that is based on one of our two papers. Together our two papers describe a first-principles “pivot-slide model” of the motion of a curling rock. The most serious error is that the “improved pivot-slide model” (Mancini and de Schoulepnikoff. Can. J. Phys. 97(12), 1301 (2019) doi: 10.1139/cjp-2018-0356 ) is based on only our first paper, whereas the most important work in our model was described in our second paper, which those authors have overlooked. Another error is that the authors claim we use constant friction, whereas we actually use a velocity-dependent formulation of the ice friction coefficient. Thirdly, the authors use a time-dependent function for the ratio of pivoting time to sliding time, whereas in our second paper, we showed from first principles that this ratio does not depend on time.
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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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.023 | 0.027 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".