Application of Montreal cognitive assessment in the patients with Parkinson's disease
Bibliographic record
Abstract
Objective To analyze the characteristics of cognitive function impairment in the patients with Parkinson's disease(PD) by Chinese version of Montreal cognitive assessment(MoCA) and to explore the application of MoCA in the patients with PD.Methods Thirty-five patients with PD were detected by MoCA and the results were analyzed.Results The total score of MoCA in patients with PD were 20.51±5.767,and there were seven patients less than 26.The incidences were different in the impairment of each cognitive domain of PD.It was indicated by the relevance analysis between each cognitive domain and total score in MoCA that attention,visual space and executive capacity were relevant closely with the total score in the scale.Conclusion MoCA could be used as a tool in clinical study of cognitive function for PD.Cognitive domain damage of PD were language,memory,visual space and executive capacity,Abstraction and attention.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".