Psychometric properties of <scp>M</scp>alay neuropsychiatry unit cognitive assessment tool among <scp>A</scp>lzheimer's disease patients in comparison to <scp>M</scp>alay <scp>M</scp>ontreal <scp>C</scp>ognitive <scp>A</scp>ssessment
Bibliographic record
Abstract
This study aims to establish psychometric properties of the Malay Neuropsychiatry Unit Cognitive Assessment Tool (Malay NuCOG) in Alzheimer's disease. NuCOG was translated to Malay language and compared with Montreal Cognitive Assessment Tool on 80 individuals. The Malay NuCOG showed good internal consistency and reliability (Cronbach's alpha = 0.895). It demonstrated 100% sensitivity and 87.5% specificity at the cutoff score of 78.50/100. The Malay NuCOG is a valid and reliable cognitive instrument that is sensitive and specific for the detection of dementia and has clinical advantages in its ability to examine individual cognitive domains.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".