Comparison of cognitive assessment in subjects with Alzheimer′ s disease between Montreal cognitive assessment Chinese version and mini-mental state examination
Bibliographic record
Abstract
Objective: To assess the cognitive function of subjects with or without Alzheimer′s disease (AD) with Chinese version of Montreal cognitive assessment (MoCA) and mini-mental state examination (MMSE) and to analyze the characteristic of Chinese version of MoCA. Method: Chinese version of MoCA was translated by Wang Wei. Fifty-six patients with AD were selected as patient group, and seventy-eight subjects without neurological disorders participated as control group.All the subjects were assessed with MoCA and MMSE and the results were analyzed. Result: There was high correlation between the scores of MoCA and MMSE (r=0.898,P0.001). To perform the assessment of Chinese version of MoCA needed to take the same time as that of MMSE. Conclusion: Chinese version of MoCA could be used as a tool in clinical study of cognitive function for AD.
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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".