Axial Signs and Magnetic Resonance Imaging Correlates in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Age-related brain changes may contribute to axial features in Parkinson's disease (PD). OBJECTIVES: To determine if ventricular volume and white matter high signal changes (WMC) are related to motor signs in PD and controls independent of age. METHODS: Patients were rated with the Unified Parkinson's Disease Rating Scale (subscore A: tremor, rigidity, bradykinesia, and facial expression; subscore B: speech and axial impairment). Steps and time taken to walk 9.144 meters were measured. Total ventricular volume (TVV) and intracranial volume (ICV) were measured on T1-weighted MRI using manual tracing software. WMC were rated on axial T2-weighted, dual-echo or FLAIR MR images using a visual scale. RESULTS: TVV (cm3) (PD: 36.48 +/- 15.93; controls: 32.16 +/- 14.20, p = 0.21) and WMC did not differ between groups (PD: 3.7 +/- 4.2; controls: 3.2 +/- 3.1, p = 0.55). Age correlated positively with ICV-corrected TVV and WMC in PD (cTVV: r = 0.48, p = 0.003; WMC: r = 0.42, p = 0.01) and controls (cTVV: r = 0.31, p = 0.04; WMC: r = 0.44, p = 0.003). Subscore B (r = 0.42, p = 0.01) but not subscore A (r = 0.25, p = 0.14) correlated with cTVV in PD. Steps and walking time correlated with cTVV and WMC in PD; cadence correlated with cTVV and steps with WMC in controls. Age-adjustment eliminated correlations. CONCLUSION: Subscore B, but not subscore A correlated positively with ventricular volume in PD, though this association was accounted for by age. Age-related brain change super-imposed on PD may contribute to axial features.
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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) | 0.001 | 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".