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Record W1978769620 · doi:10.3200/jmbr.38.1.45-59

Motor Deficits in Parkinsonian Reaching: Dopa-Sensitivity Influenced by Real-World Task Constraint

2006· article· en· W1978769620 on OpenAlexaff
Jon B. Doan, Ian Q. Whishaw, Sergio M. Pellis, Oksana Suchowersky, Lesley A. Brown

Bibliographic record

VenueJournal of Motor Behavior · 2006
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of CalgaryUniversity of Lethbridge
Fundersnot available
KeywordsTask (project management)Constraint (computer-aided design)PsychologyNeuroscienceSensitivity (control systems)Cognitive psychologyPhysical medicine and rehabilitationMedicineMathematicsEngineering

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) patients can perform many daily activities, but movement deficits are evident. Those deficits may be increased when the required movement is constrained in accuracy. Variable improvements in performance with PD medication have been demonstrated, and sensitivity to task constraint has been evident in some studies. The authors quantified both specific movement deficits and improvements for PD patients in a reaching task. PD patients (N=8) both on and off medication showed a need for greater ongoing control in movements with higher task-accuracy constraints. Increased task-accuracy constraints further compromised movement timing and structure among PD patients who were off medication, suggesting that unmedicated PD patients may typically compensate by using more conscious control of movement, resulting in increased slowing and segmentation of components when higher task accuracy is required.

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)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.018
GPT teacher head0.282
Teacher spread0.264 · 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

Citations16
Published2006
Admission routes1
Has abstractyes

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