Capturing the Essence of Speed Skating and the Skate Technique in Cross-Country Skiing
Bibliographic record
Abstract
Speed skating and the skate technique in cross-country skiing are activities in which ski/skate positioning governs the propulsive impulse and the direction of travel. Although it is known anecdotally that the ski/skate placement becomes more aligned with the direction of travel as speed increases, the optimal placement is not known. The aim of this study was to develop a theoretical model that gives the ski/skate placement that maximizes the average speed. The dilemma occurs because the direction of the ski/skate determines the path of travel, while propulsion can only be produced perpendicular to the skate/ski. The theoretical model was based on the impulse-momentum relationship, air resistance was ignored, and gliding resistance was assumed constant and along the direction of the skate/ski. Only steady state gliding was considered, meaning that the average speed in the direction of desired travel was constant. The velocity of a new stride is influenced by the gliding velocity of the previous stride and the velocity generated by the impulse in the transition from one skate/ski to the other. Based on these assumptions, two equations were derived for the average forward velocity: one for speed skating and skiing without propulsion from the poles, and a second for skiing with propulsion from the poles. The model was used to predict the optimal skate/ski angles relative to the desired direction of travel that maximize the average forward speed given an athlete’s mass, impulse from the legs, and impulse from the arms. In agreement with experimental observations, the model predicts that the orientation of ski/skates becomes more aligned with increasing speed of travel and becomes parallel to the direction of travel when the entire forward propulsion is derived from the poles. The detailed predictions now need testing against careful experimental measurements in the field.
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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 | 0.006 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".