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Record W2082409843 · doi:10.1097/pep.0000000000000109

Reliability of Measuring Hip and Knee Power and Movement Velocity in Active Youth

2015· article· en· W2082409843 on OpenAlexaff
Joanne Parsons, Michelle M. Porter

Bibliographic record

VenuePediatric Physical Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of ManitobaManitoba Arts CouncilResearch ManitobaManitoba Health
Fundersnot available
KeywordsSittingReliability (semiconductor)Power (physics)Physical medicine and rehabilitationMuscle powerDynamometerPhysical therapyKnee flexionSimulationMedicineComputer sciencePhysicsEngineeringAutomotive engineering

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to determine the reliability of measuring neuromuscular power and movement velocity of the hip and knee in young, active individuals using an isokinetic dynamometer. METHODS: Peak power, average power, and peak velocity (PV) data were recorded for the hip in the standing position and the knee in the sitting position in 52 youth aged 10 to 14 years on 2 occasions approximately 1 week apart. RESULTS: The PV measures demonstrated the best absolute reliability of all variables tested (coefficients of variation of the typical error [CV(TE)] = 5.0%-8.5%; standard errors of measurement = 18.1-21.1°/s). Hip flexion and knee extension peak power and average power exhibited acceptable reliability (CV(TE) = 8.7%-10.8%) compared with the other isokinetic tests (CV(TE) = 16.9%-32.8%). CONCLUSIONS: Peak velocity appears to be a reliable means of indirectly measuring neuromuscular power in active youth, whereas direct measurement of power is only reliable for certain movements.

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 score0.032
Threshold uncertainty score0.275

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 head0.047
GPT teacher head0.281
Teacher spread0.234 · 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

Citations9
Published2015
Admission routes1
Has abstractyes

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