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Record W2051585437 · doi:10.1080/15438627.2014.881819

The Temporospatial and Kinematic Characteristics of Typical Tai Chi Movements: Repulse Monkey and Wave-hand in Cloud

2014· article· en· W2051585437 on OpenAlexaff
Nok-Yeung Law, Jing Xian Li

Bibliographic record

VenueResearch in Sports Medicine · 2014
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsKinematicsPhysical medicine and rehabilitationMedicinePhysics

Abstract

fetched live from OpenAlex

Tai Chi movements share many similar biomechanical features with normal walking. The purpose of the study was to examine and to compare the temporospatial and kinematic features of two typical Tai Chi movements with forward walking. Experienced male Tai Chi practitioners (n = 15) between the ages of 65 to 75, performed 'Repulse Monkey (RM)', 'Wave-hand in Cloud (WHIC)', and forward walking. The results showed that stride width was larger for WHIC compared with walking; double-support time was longer for RM while both Tai Chi movements spent less time in single-support. The Tai Chi movements elicit larger vertical and mediolateral displacement of the centre of mass compared with walking. During RM and WHIC, the knees remained flexed while RM had notably larger abduction and adduction of the knee joint. The gentle and fluid Tai Chi movements have unique biomechanical features that may result in special training to postural control capacity.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.054
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.419
Teacher spread0.364 · 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

Citations42
Published2014
Admission routes1
Has abstractyes

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