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Record W2045056034 · doi:10.2466/23.25.pms.118k12w5

From Specific Training to Global Shift of Manual Preference in Kung Fu Experts

2014· article· en· W2045056034 on OpenAlexaff
Rodrigo S. Maeda, Rosana Machado de Souza, Luís Augusto Teixeira

Bibliographic record

VenuePerceptual and Motor Skills · 2014
Typearticle
Languageen
FieldNeuroscience
TopicHemispheric Asymmetry in Neuroscience
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPreferenceHand preferencePsychologyPerspective (graphical)Cognitive psychologyAthletesLateralityFood preferenceDevelopmental psychologyComputer sciencePhysical therapyArtificial intelligenceStatisticsMathematicsMedicine

Abstract

fetched live from OpenAlex

Manual preference and intermanual performance asymmetry have been approached from a multidimensional and dynamic perspective. A point of interest from that approach is the role of lateralized motor experiences on handedness. In this study, intermanual performance asymmetry in sport-specific movements and manual preference in daily living tasks were compared between Kung Fu athletes and novices. Analysis of movement time in the performance of interlaterally symmetric and asymmetric movement patterns showed smaller intermanual performance asymmetry in experts. Analysis of manual preference using the Edinburgh Handedness Inventory indicated that experts presented predominantly weak or moderate strength of right hand preference. Novices, conversely, were found to have predominantly strong right hand preference. These results suggest that extensive bimanual training by experts leads to a global shift of manual preference, affecting hand selection in distinct tasks.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.047
GPT teacher head0.287
Teacher spread0.240 · 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 designBench or experimental
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

Citations11
Published2014
Admission routes1
Has abstractyes

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