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Record W7027955661

Efectos del entrenamiento en slackline sobre la resistencia del core y el equilibrio dinámico

2021· article· en· W7027955661 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTrunkCore stabilityExcursionPlankBalance testCore (optical fiber)
DOInot available

Abstract

fetched live from OpenAlex

Slackline challenges balance by walking on a tensioned strap, where the trunk muscles help to maintain or regain balance. This study aimed to compare a cohort of individuals who regularly practiced slackline and physically inactive individuals on core endurance (CE) and dynamic balance (DB) and to determine whether CE is associated with years of slackline practice. Nine individuals (7 men) who practiced slackline regularly (SG; age= 24.5±3.6 years) and nine physically inactive individuals (7 men) (CG; age= 23.2±3.3 years) were compared. CE was assessed with the McGill battery (trunk flexor, extensor, and side-bridge test) and the plank test. DB was measured with the modified star excursion balance test in stable and unstable conditions. The SG maintained a 36.2% and 45% longer time in left lateral bridge (p=.049) and plank (p=.031), respectively, compared to the CG. The distance achieved in the stable DB test was similar between groups, but in unstable condition was 37.8% greater (p=.016) in SG in both legs and 46.6% greater in the non-dominant leg (p=.039) compared to CG. The SG showed a correlation between years of slackline practice and flexor (r=.674; p=.046), right lateral (r=.765; p=.016) and left (r=.730; p=.026) trunk endurance. In conclusion, those who practice slackline maintain a longer time in the plank and left lateral bridge test and achieve a higher reach distance in unstable DB compared to physically inactive individuals who do not practice slackline.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.895
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.248
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.

Study designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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