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Record W2923406584 · doi:10.1080/00222895.2019.1587351

Attention Is Required to Coordinate Reaching and Postural Stability during Upper Limb Movements Generated While Standing

2019· article· en· W2923406584 on OpenAlexafffund
Jill Dierijck, Michael Kennefick, Jonathan D. Smirl, Brian H. Dalton, Paul van Donkelaar

Bibliographic record

VenueJournal of Motor Behavior · 2019
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhysical medicine and rehabilitationTask (project management)KinematicsMovement (music)PsychologyCenter of pressure (fluid mechanics)MedicineEngineering

Abstract

fetched live from OpenAlex

In the present study we investigated how attention contributes to the interaction between reach planning and execution, and postural control. Reaching movements were generated while standing and were performed either in isolation or in conjunction with a secondary reaction time (RT) task. In addition, to better understand how online movement control is affected by this interaction, the reaching movements could be unexpectedly perturbed medial-laterally. Postural kinetic, arm kinematic and RT, and secondary RT measures were used to characterize the responses. Results indicate task performance worsened when both the reaching and secondary tasks were completed simultaneously. Our results imply the generation of reaching movements while standing requires attentional resources to properly coordinate the interaction between the reaching task and postural control.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.046
GPT teacher head0.275
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 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

Citations15
Published2019
Admission routes2
Has abstractyes

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