On-ice acceleration as a function of the Wingate anaerobic test and a biomechanical assessment of skating technique in elite ice hockey players
Why this work is in the frame
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Bibliographic record
Abstract
Success in ice hockey depends on an individual?s ability to accelerate from a standing \nstart or change direction and continue skating quickly and efficiently. Previous research to \ndetermine those factors which had the greatest contribution to on-ice acceleration was limited to \ntwo-dimensional biomechanical analyses of skating technique, without regard for the influence \nof physiological measures. The purpose of the present study was therefore to predict on-ice \nacceleration using peak anaerobic power from a Wingate test and kinematic variables from a \nthree dimensional analysis of the biomechanics of skating technique. A sub-purpose of the \npresent study was to examine the variability of skating technique at the elite level. The \nparticipants in this research study were thirty-seven ice hockey players from the Florida Panthers \nand Los Angeles Kings of the National Hockey League participating in the 1999 Prospects Camp \nin Thunder Bay, Ontario. The players completed a thirty second, maximal intensity Wingate \nanaerobic cycle ergometer test against a resistance of 0.095 kg-kg bodyweight-1. Peak anaerobic \npower was calculated and recorded as the highest anaerobic power value (number of flywheel \nrevolutions) produced during any of the five-second intervals. One week following the Wingate \nanaerobic test, the players performed two maximal, on-ice accelerations over a distance of \ntwenty meters, while being taped by two, Panasonic? CL-350 digital cameras mounted on Peak \nPerformance? pan/tilt heads. The Peak Performance? 3D Video Analysis System and a 23- \npoint spatial model were used to extract the raw coordinates for the fastest of the two trials for \neach player, as measured by a photoelectric timer. The system was then used to smooth the raw \ndata from both camera views and to combine the smoothed data to produce a three-dimensional \nimage. Center of mass and kinematic variables of interest were measured at push-off and \ntouchdown for the first five strides.
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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 | 0.000 | 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 | 0.000 |
| 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 it