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Record W2179728435 · doi:10.1002/dev.21386

How the mode of action affects evidence of planning and movement kinematics in aging: End‐state comfort in older adults

2015· article· en· W2179728435 on OpenAlexafffund
Sara M. Scharoun Benson, Dave A Gonzalez, Éric Roy, Pamela J. Bryden

Bibliographic record

VenueDevelopmental Psychobiology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyStimulus (psychology)Cognitive psychologyKinematicsPhysical medicine and rehabilitationDevelopmental psychologyMotor controlTask (project management)AudiologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Motor deficits are commonly observed with age; however, it has been argued that older adults are more adept when acting in natural tasks and do not differ from young adults in these contexts. This study assessed end-state comfort and movement kinematics in a familiar task to examine this further. Left- and right-handed older adults picked up a glass (upright or overturned) as if to pour water in four modes of action (pantomime, pantomime with image/cup as a guide, actual grasping). With increasing age, a longer deceleration phase (in pantomime without a stimulus) and less end-state comfort (in pantomime without a stimulus and image as a guide) was displayed as the amount of contextual information available to guide movement decreased. Changes in movement strategies likely reflect an increased reliance on feedback control and demonstration of a more cautious movement. A secondary aim of this study was to assess hand preference and performance, considering conflicting reports of manual asymmetries with age. Performance differences in the Grooved Pegboard place task indicate left handers may display a shift towards right handedness in some, but not all cases. Summarizing, this study supports age-related differences in planning and control processes in a familiar task, and changes in manual asymmetries with age in left handers.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.242

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 communication0.0000.000
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 head0.086
GPT teacher head0.328
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

Citations15
Published2015
Admission routes2
Has abstractyes

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