Normative Data of the Montreal Cognitive Assessment in the Greek Population and Parkinsonian Dementia
Bibliographic record
Abstract
The Montreal Cognitive Assessment (MoCA) is a brief cognitive instrument for the measurement of dementia. The aim of the present study is to provide normative data for the MoCA test in the Greek speaking population and to measure its validity in a clinical group of parkinsonian dementia participants. A total of 710 healthy Greek speaking participants and 19 parkinsonian dementia participants took part in the study. Both, the MoCA test and a neuropsychological test battery (digit span, semantic verbal fluency, phonemic verbal fluency, Color Trails Test) were administered to the normative and clinical samples. The test was found to correlate with all neuropsychological tests used in the test battery and it showed high discriminant validity (optimal screening cutoff point = 21, sensitivity = 0.82, specificity = 0.90) in the parkinsonian dementia participants. Further research is needed to use it in larger clinical samples and in different neurological diseases.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".