Parkinson's disease patients experiencing peak-dose dyskinesia redistribute involuntary movements throughout their body to improve motor control
Bibliographic record
Abstract
INTRODUCTION: In Parkinson's disease (PD), dyskinesia is considered a major side effect of dopamine replacement therapy. Nevertheless, many patients with dyskinesia function adequately. OBJECTIVE: To study objectively dyskinesia phenomenology in order to understand why or how patients with dyskinesia are still able to perform motor tasks. METHODS: Patients with and without dyskinesia, as well as healthy older adults, performed a geostationary task during which they attempted to stabilize a glass of water at eye level. Dyskinesia amplitude displayed by each body segment was extracted from accelerometers, and its distribution among the segments, analyzed. RESULTS: Patients experiencing dyskinesia initially distributed most of their dyskinesia away from the segments directly involved in the task. With time, this distribution shifts back towards the hand. CONCLUSION: Our results suggest that patients developed a strategy of involuntary movement's redistribution to attenuate their functional impact on voluntary movements. However, this strategy can only be maintained for a certain period before "re-emerging" dyskinesia occurs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".