Validation of the alpine skiing 90 seconds box jump field test and prediction of power output
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to validate the alpine ski racing 90 s box jump field-test (BJ90) with the 90 s Wingate test (W90).METHODS: Fifteen elite alpine ski racers were tested on the BJ90 (0.45 m × 0.75 m × 0.9 m) and the W90 (Ergomedic 894 E Monark; Monark AB, Varberg, Sweden) test in a random order. The number of hits on the BJ90 was written down every 15 s and for the W90 the load (7.5% of body weight) was manually dropped once the subjects reached maximum RPM without resistance. Correlations and partial correlations were calculated with a 2-tailed Pearson correlation analysis. A stepwise forward regression analysis was also performed.RESULTS: Results present significant (P<0.05) correlations and partial correlations adjusted for body weight between the total number of hits on the BJ90 and W90 peak W, peak W/kg, mean W and mean W/kg as well as with the number of hits and W90 Mean W and mean W/kg between each 15 s time slot. A linear regression predictive equation for mean relative power (W/kg) generated from the BJ90 was established: mean relative power (W/kg)=0.055*total hits+1.080 (r=0.79, P<0.001; total hits with mean W/kg). A stepwise forward regression equation for mean absolute power (W) generated from the BJ90 was also established: mean absolute power (W)=2.305*number of hits+5.081*body weight in kg-1 -169.8 (R=0.964, P<0.001, SEE=23.56).CONCLUSIONS: Practitioners could use the BJ90 to assess alpine skiers lower body power as previous research showed that both are correlated with performance and are able to discriminate skier level.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".