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Record W2092477595 · doi:10.2147/oajsm.s68337

Influences of a yoga intervention on the postural skills of the Italian short track speed skating team

2015· article· en· W2092477595 on OpenAlexaff
Philippe Fait, Jean‐François Brunelle, Eric L.R. Bédard, K. Gouadec, Sebastien Blais-Coutu

Bibliographic record

VenueOpen Access Journal of Sports Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSpeed skatingPhysical medicine and rehabilitationPhysical therapyMedicinePsychologySimulationComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION: In preparation for a short track speed skating season, eight men and seven women were given yoga sessions during an 8-week high volume training cycle. The sessions were planned according to the postural aspects specific to short track speed skating technical requirements. Three specific goals were selected for the intervention: 1) to observe whether the practice of yoga as postural training could improve the efficiency and the athlete's repertoire along the muscular synergies solicited in the short track speed skating specific technique; 2) to enhance and diversify the motor time-on-task of athletes without changing the prescription of other training stimulus; and 3) to lower the risk of injury during periods with high volumes of training. METHODS: A total of 36 sessions of yoga were given. Three postural tests were administered before and after the intervention with 14 angles analyzed. Non-parametric Wilcoxon test was used to compare angles' variations. RESULTS: The 36 yoga sessions totalized 986 minutes of motor time-on-task, registering a proportion of 30% of the global motor time-on-task of the training cycle. Improvements were found in eleven of the 14 angles measured when comparing pre- and post-postural tests (P-value from 0.01 to 0.005). During the 8 weeks, excepting traumatic injuries due to short track speed skating accidents, no skaters suffered injuries linked to the high volume of training. Following the intervention, coaches noticed, following their on-ice feedbacks, an adjustment in the efficiency of the skating technique, in particular regarding hip dissociation. CONCLUSION: These results suggest that yoga could be inserted into out-of-season training cycles, even in a high volume training cycle. Planned with the decision training tools, it allows athletes to diversify their motor time-on-task by integrating a new functional range of generic movements with the solicitation of neuromuscular synergies related to the specificity of their sport.

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)0.003
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 score0.036
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.100
GPT teacher head0.422
Teacher spread0.323 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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