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Record W2790662738 · doi:10.5539/ass.v14n4p65

The Level of Mindfulness, Hand-eye Coordination and Strength among Elite Fencers

2018· article· en· W2790662738 on OpenAlexvenueno aff
Mousa Ahamad, Bilal Saada, Qusai Alshamaileh, Mahmoud Abusamra, Aida A. Al-Awamleh

Bibliographic record

VenueAsian Social Science · 2018
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsnot available
FundersUniversity of Jordan
KeywordsMindfulnessPsychologyEye–hand coordinationEliteDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

The present study aimed to investigate the strength level of mindfulness and hand-eye coordination among elite fencers, also to determine whether the gender differences in mindfulness were existed, The subjects of this study consisted of sixteen elite fencers, Five Facet Mindfulness Questionnaire (FFMQ) Arabic version used to assess mindfulness (FFMQ), also handgrip dynamometer to assess strength and Hand-eye coordination manual dexterity to measure hand-eye coordination.The research used the steadiness toaster, hold type model 32011 to assess eye - hand coordination. The participants Study sample consists of sixteen national fencers (Jordanian National Team), aged between (14-23) years. The results indicated that the level of mindfulness was moderated and there is no statistically significant relationship between strength, Mindfulness and hand-eye coordination. Furthermore, gender differences were observed regarding strength.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.042
GPT teacher head0.351
Teacher spread0.309 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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