Analysis of neuropsychological characteristics for old patients with vascular mild cognitive impairment by MoCA scale.
Bibliographic record
Abstract
Objective To study the neuropsychological characteristics for old patients with vascular mild cognitive impairment (vMCI) with MoCA scale in order to provide science evidence for early discovery, diagnosis and intervention of vMCI. Methods The vMCI patients who accepted therapy in our hospital from January 2010 to May 2011 were surveyed by Montreal Cognitive Assessment (MoCA). Results The accuracy rate of MoCA was 97.3%. Age, educational level and occupation significantly influenced the score of MoCA (P 0.05). The score of delayed remember, attention and visual space were the lowest percentage of their own total score, as 31.40%, 65.17% and 69.00%. Conclusion MoCA was a good tool to screen the vMCI, and it should be widely applied. In addition, the neuropsychological characteristics of vMCI were heavier damage in visual space and executive ability, attention and delayed memory and so on.
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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 | 0.001 |
| 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".