Vascular <scp>P</scp>arkinsonism: <scp>D</scp>econstructing a <scp>S</scp>yndrome
Bibliographic record
Abstract
Progressive ambulatory impairment and abnormal white matter (WM) signal on neuroimaging come together under the diagnostic umbrella of vascular parkinsonism (VaP). A critical appraisal of the literature, however, suggests that (1) no abnormal structural imaging pattern is specific to VaP; (2) there is poor correlation between brain MRI hyperintensities and microangiopathic brain disease and parkinsonism from available clinicopathologic data; (3) pure parkinsonism from vascular injury ("definite" vascular parkinsonism) consistently results from ischemic or hemorrhagic strokes involving the SN and/or nigrostriatal pathway, but sparing the striatum itself, the cortex, and the intervening WM; and (4) many cases reported as VaP may represent pseudovascular parkinsonism (e.g., Parkinson's disease or another neurodegenerative parkinsonism, such as PSP with nonspecific neuroimaging signal abnormalities), vascular pseudoparkinsonism (e.g., akinetic mutism resulting from bilateral mesial frontal strokes or apathetic depression from bilateral striatal lacunar strokes), or pseudovascular pseudoparkinsonism (e.g., higher-level gait disorders, including normal-pressure hydrocephalus with transependimal exudate). These syndromic designations are preferable over VaP until pathology or validated biomarkers confirm the underlying nature and relevance of the leukoaraiosis. © 2015 International Parkinson and Movement Disorder Society.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".