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Record W2118324232 · doi:10.1123/apaq.24.4.352

Older Adults Demonstrate Reduced Performance in a Fitts’ Task Involving Cervical Spine Movement

2007· article· en· W2118324232 on OpenAlexaff
Steven Passmore, Jeanmarie R. Burke, Jim Lyons

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2007
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhysical medicine and rehabilitationTask (project management)Cervical spineMovement (music)PopulationPsychologyAudiologyRange of motionAge groupsReplicatePerceptionMedicinePhysical therapyMathematicsDemographyStatisticsNeuroscienceSurgeryPhysics

Abstract

fetched live from OpenAlex

A discrete aiming head movement task was developed to replicate Fitts'movement paradigm. Movement time (MT) differences between young (age range 24-29 years, n = 8) and old adults (age range 75-85 years, n = 8) were examined. Cervical spine (CS) range of motion (ROM) was recorded.A head mounted motion capture device was used to evaluate task performance. Three amplitudes and three target widths generated nine indexes of difficulty (IDs). Global ROM was decreased in old adults. The ID and MT relationship was maintained with age; however, old adults were slower, more variable, and more affected by ID. Variations in target size were used as the accuracy variable for both groups. As target size increased, the old population overshot their endpoint. These data support the hypothesis that, besides musculoskeletal slowing with age, there may be age-related deterioration of central processing, planning, or perception mechanisms.

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 score0.002
Threshold uncertainty score0.005

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 head0.016
GPT teacher head0.246
Teacher spread0.230 · 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
Published2007
Admission routes1
Has abstractyes

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