Comparison of alternative version of The Montreal Cognitive Assessment (MoCA-CZ 2) with its basic version (MoCA-CZ 1).
Bibliographic record
Abstract
The thesis discusses screening psychodiagnostics with special attention given to amnestic mild cognitive impairment and Alzheimer's disease. The theoretical part describes the concepts of healthy aging and the disorders of cognitive functions. It provides an overview of the screening methods most frequently used in the Czech Republic and the description of MoCA test. It also briefly outlines the issues of retesting in psychodiagnostics. The objective of the empirical part of the work was to verify the psychometric characteristics of the Czech alternative version MoCA-CZ and to evaluate whether it is possible to use this test in practice. The evaluation also includes a comparison of the new version with the already established standard version of MoCA-CZ test. We assigned standard and alternative versions of MoCA-CZ in a 2-month interval to 59 healthy volunteers, 35 patients with mild cognitive impairment and 41 patients with dementia resulting from Alzheimer's disease. We found a strong correlation between alternative and standard version of MoCA-CZ test. We confirmed statistically significant differences in the average scores between individual research groups in both versions of the test. We proved that the alternative version MoCA-CZ 2 is reliable. And we demonstrated that the administration and...
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".