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Record W3186404638 · doi:10.3390/sports9080105

Normative Reference of the Single Leg, Medial Countermovement Jump in Adolescent Youth Ice Hockey Players

2021· article· en· W3186404638 on OpenAlexafffund
Anthony S. Donskov, Jeffrey S. Brooks, James P. Dickey

Bibliographic record

VenueSports · 2021
Typearticle
Languageen
FieldMedicine
TopicWinter Sports Injuries and Performance
Canadian institutionsWestern University
FundersWestern University
KeywordsIce hockeyNormativeJumpPsychologyPhysical medicine and rehabilitationMedicinePolitical sciencePhysicsLaw

Abstract

fetched live from OpenAlex

Functional performance tests provide quantitative information on specialized sport movements and are important for documenting training and fatigue. The single leg, medial countermovement jump provides objective measures of frontal plane force, velocity and power, and is relevant for ice hockey players given the similar lateral movement to ice skating. This study measured normative single leg, medial countermovement jump parameters (i.e., vertical and lateral maximum force, average concentric power and average concentric power during the last 100 ms) amongst male youth ice hockey players and assessed interlimb asymmetry in these healthy athletes. Ninety-one elite youth players participated in the study. Participants completed three right and three left jumps. Non-parametric tests were performed to evaluate between-jump and between-group comparisons. Many differences in jump force and power parameters were observed between the 10U/11U and 12U/13U age groups, and the 12U/13U and 14U/15U age groups, but differences were not as consistent between older or younger players. The average asymmetry index for each age group was less than 15% for force parameters, while the power parameters had larger asymmetry indices (between 9% and 22%). Our results provide age-specific reference values and asymmetry indices for male elite youth ice hockey players aged 10-18 years performing the single leg, medial countermovement jump.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.259
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations4
Published2021
Admission routes2
Has abstractyes

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