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Record W2596327116 · doi:10.1080/02640414.2017.1300314

Effects of running experience on coordination and its variability in runners

2017· article· en· W2596327116 on OpenAlexaff
Pablo Floría, Alberto Sánchez‐Sixto, Reed Ferber, Andrew J. Harrison

Bibliographic record

VenueJournal of Sports Sciences · 2017
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsRunning Injury ClinicUniversity of Calgary
Fundersnot available
KeywordsKnee flexionAnklePhysical medicine and rehabilitationPhysical therapyAnkle dorsiflexionKinematicsGround reaction forceGaitMedicineRange of motionAnatomyPhysics

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the differences in coordination variability in running gait between trained runners and non-runners using continuous relative phase (CRP) analysis. Lower extremity kinematic data were collected for 22 participants during the stance phase. The participants were assigned to either a runner or non-runner group based on running volume training. Segment coordination and coordination variability were calculated for selected hip-knee and knee-ankle couplings. Independent t-tests and magnitude-based inferences were used to compare the 2 groups. There were limited differences in the CRP and its variability among runners and non-runner groups. The runners group achieved moderately lower coordination compared with non-runners group in the phase angle for hip abduction/adduction and knee flexion/extension. The runners tended to show moderately lower coordination variability in the phase angle for knee flexion/extension and subtalar inversion/eversion in comparison to non-runners group. These results suggested that levels of experience as estimated from weekly training volume had little influence on coordination and its variability.

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)0.000
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 score0.411
Threshold uncertainty score0.145

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.261
Teacher spread0.245 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

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