Bibliographic record
Abstract
Vascular parkinsonism (VP) accounts for 2.5-5% of all cases of parkinsonism in various population based and clinical cohort studies. VP develops as a result of ischaemic cerebrovascular disease, so aetiologically it is classified as secondary parkinsonism. It has been variably referred to in the literature as arteriosclerotic parkinsonism, vascular pseudo-parkinsonism, and lower body parkinsonism. The most important consideration while making a diagnosis of VP should be to differentiate VP from Parkinson's disease (PD) because of prognostic and therapeutic implications. The salient clinical features in VP which differentiate it from PD are presentation with postural instability and falls rather than with upper limb rest tremor or bradykinesia; short shuffling parkinsonian gait in VP is accompanied by a wider base of stance and variable stride length (parkinsonian-ataxic gait), absence of festination, frequent occurrence of pyramidal signs, and early subcortical dementia. In a patient where the clinical features are suggestive of VP the clinical diagnosis can be supported by demonstration of diffuse white matter lesions and/or strategic subcortical infarcts in the MRI of the brain. The therapeutic options in VP are limited to levodopa, and a poor or non-sustained response to levodopa is another differentiating feature between VP and PD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".