Pain in Parkinson's disease
Bibliographic record
Abstract
Pain may precede the diagnosis in Parkinson's disease (PD). The goal of this study was to assess the pain in a group of 20 females and 30 males with PD, after excluding co-morbidities as causes. It was used the following tools: Unified Parkinson's Disease Rating Scale, McGill questionnaire and Beck Depression Inventory. In 27 patients (54%), the pain was associated with PD, occurring in 22 (44%) in the off period and 5 (10%) in both on and off periods. The off period resulted in an increased frequency of pain, which was related to stiffness. There was no association between pain and tremor in off period, neither between pain and Modified Hoehn and Yahr stage, nor the Schwab and England scale. It was not observed an association between pain and depression, neither between pain and dyskinesia. It was noticed the improvement in pain in 16 patients with levodopa (59.26%).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".