The tools of the trade: A state of the art “How to Assess Cognition” in the patient with Parkinson's disease
Bibliographic record
Abstract
Cognitive impairment in Parkinson's disease is heterogeneous both in severity and pattern and subject to influences both integral to and external to the disease. Diagnostic Criteria have been developed by the Movement Disorders Society that help to guide clinicians and researchers to an accurate diagnosis of Parkinson's disease - mild cognitive impairment or Parkinson's disease dementia. To operationalize these criteria, and to assess the pattern and severity of cognitive dysfunction we need: (1) Valid measures of cognitive abilities covering the major domains of cognition, (2) amethod to determine whether or not the performance represents a decline from a person's previous level of functioning, and (3) an assessment of how the individual's cognitive abilities enable (or disable) function in day to day activities. This paper will discuss the methods of assessment and the measures that can be used to make a comprehensive assessment of cognition in Parkinson's disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".