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Record W3014575487

Bimanual joint action: Correlated timing of "bimanual" movements accomplished by two people

2016· article· en· W3014575487 on OpenAlexaff
Melanie Y. Lam, Jarrod Blinch, Elizabeth M. Connors, Jon B. Doan, Claudia L. R. Gonzalez

Bibliographic record

VenueJournal of Exercise, Movement, and Sport · 2016
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of LethbridgeSt. Francis Xavier University
Fundersnot available
KeywordsMovement (music)Joint (building)PsychologyPhysical medicine and rehabilitationCoupling (piping)Cognitive psychologyCommunicationMedicineEngineeringAcousticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Many actions at work or play require carefully coordinated movements from a pair of performers. At the individual level, temporal coordination of the limbs has been observed in pointing movements even when made to targets of different amplitudes. Timing of the arms is not independent; rather there is a natural temporal coupling. The aim of this experiment was to investigate whether the temporal characteristics of pointing movements can be observed under joint conditions. Sixteen pairs of participants made short and long, unimanual and pointing movements. In the unimanual and solo conditions, participants made the movements alone. In the joint condition, each participant contributed one arm to the joint bimanual movements. Temporal coupling and correlation between the arms were examined. Pointing movements were strongly coupled in the solo condition, but they were not coupled in the unimanual solo and joint conditions. The initiation and termination of the arms were not correlated in the unimanual solo condition (initiation r = .01, termination r = .03). Small-to-medium correlations (r = .19, r = .24) were observed in the joint condition and found to be significantly larger than the unimanual solo condition (p Acknowledgments: This research was funded NSERC

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.497

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 studies0.0000.000
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.277
Teacher spread0.242 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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