Correlation analysis about Chinese cognitive assessment scale and Mini-mental state examination in the clinic test
Bibliographic record
Abstract
Objective To Explore correlation and sensitivity about Chinese cognitive assessment scale(MOCA) and Mini-mental state examination(MMSE) in the clinical test.Methods 150 cases of Hospitalized and clinic patients were enrolled.Two kinds of test scales were used to test patients.Results The total score of MOCA was 13.28±7.23,and MMSE was 19.83 ± 7.52.Both wwere closely relevant(r = 0.871).Cultural level and age of patients had significant effect on MOCA scores(P=0.000).Contribution values of Each MOCA's project as follows: attention,orientation,language,visual space,name,delayed memory,abstract thinking.Each items have significantly influenced to MOCA's scores(P=0.000).Conclusion MOCA applies clinical cognitive assessment,the difficulty of clinical is higher than MMSE,the evaluation of cognitive ability in mild cognitive impairment(MCI) patients is more sensitive than MMSE.But both are influenced by cultural factors and age.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".