Cognitive screening tests and their potential to detect cognitive impairment in neurodegenerative diseases
Bibliographic record
Abstract
Screening of global cognitive performance is of great importance in the detection of early cognitive impairment in neurodegenerative diseases. In contrast to complex neuropsychological assessment, cognitive screening tests offer some advantages as saving time or finance and administration of screening tests makes lower demands on clinicians. Validation of cognitive screening tests for specific diagnostic groups of patients is necessary as well as Czech normative studies that enable an objective evaluation of the cognitive performance of Czech patients. In the theoretical part, we presented the syndrome of mild cognitive impairment as a pre-dementia state in neurodegenerative diseases. We focused on the assessment of mild cognitive impairment and using five different cognitive screening tests (Mini-Mental State Examination, Montreal Cognitive Assessment, Dementia Rating Scale 2. edition, Frontal Assessment Battery, Clock Drawing Test) in the detection of cognitive impairment. Then we focused on Parkinson's disease (PD), especially on the evolution of different stages of cognitive deficit in PD and their detection by cognitive assessments. The empirical research included studies analyzing the potential of the five cognitive screening tests to detect mild cognitive impairment. We provided results...
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".