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Validation Of The Alpine Ski Racing 90 Seconds Box Jump Field Test

2020· article· en· W3042122397 on OpenAlexaff
Vincent D. Carey, Pierre-Marc Ferland, J E Charron, Viviane Marcotte L'Heureux, Yannick Hogue-Tremblay, Philippe Roy, Alain Steve Comtois

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2020
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMathematicsJumpVertical jumpStatisticsStatistical significancePhysics

Abstract

fetched live from OpenAlex

Practitioners have utilized sport specific alpine ski racing field tests for lower limb power assessment for many years. PURPOSE: The purpose of this study was to validate the alpine ski racing 90 s box jump field test with the 90 s Wingate. METHODS: Elite alpine ski racers (n=15) were tested during their annual post-season physical testing combine. The box 90s box jump test was conducted on a foam plyo box of 0.45m x 0.75m x 0.9m (14 kg Plyosoft box from Escape Fitness). Subjects started at one side of the box and had to do a side jump and make contact with the top of the box and then jump back down to the other side back and forth. Final score being the total number of hits in 90 s. The Wingate test was conducted on a cycle ergometer (Ergomedic 894 E Monark). Subjects had to pedal with no resistance until they reached maximum RPM (about 5-10 s). The load (7.5% of bodyweight) was then manually dropped and subjects had to pedal at a maximal effort for 90 s. Wingate peak and mean power was measured in W and W/kg of bodyweight. Both tests were performed in a random order. Correlations between the different test results were calculated with a 2-tailed Pearson correlation analysis. Statistical significance was set at p<0.05. Subject characteristics are presented as means and standard deviations. RESULTS: Results present significant (p<0.05) correlations between the total number of hits on the 90 s box jump and Wingate peak W (r=0.73), peak W/kg (r=0.68), mean W (r=0.77) and mean W/kg (r=0.79). Results also present significant correlations with the number of hits between the following time slots: 0-15 s mean W (r=0.49), 0-15 s mean W/kg (r=0.72), 15-30 s mean W (r=0.66), 15-30 s mean W/kg (r=0.71), 30-45 s mean W (r=0.59), 30-45 s mean W/kg (r=0.66), 45-60 s mean W (r=0.82), 45-60 s mean W/kg (r=0.77), 60-75 s mean W (r=0.83), 60-75 s mean W/kg (r=0.65), 75-90 s mean W (r=0.75) and 75-90 s mean W/kg (r=0.71). A predictive regression equation using the total hits during the 90s Box Jump Test was established, where mean W/kg = 0.055*Total Hits + 1.080 (r=0.79, p<0.01; Total Hits with mean W/kg). CONCLUSIONS: The 90s box jump test is well correlated to the power output obtained with the Wingate test. Nonetheless, further research should include subjects at the national and international level in order to update the formula.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.279
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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