Determining an appropriate cutting score for indication of impairment on the Montreal Cognitive Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE/METHODS: The Montreal Cognitive Assessment (MoCA) is a brief yet comprehensive cognitive instrument used to assess level of impairment in neurological populations. The purpose of the present study was to assess the ability of the MoCA to detect cognitive impairment in a veteran patient population referred for neuropsychological testing and to determine optimal cutoff scores on the MoCA when compared with widely used neuropsychological measures. RESULTS: Using receiver operator characteristic (ROC) analyses, the findings indicate that the optimal cutoff score to detect impairment (i.e., ≤ 20) in the present sample was notably lower than that suggested by others. CONCLUSIONS: Use of the previously suggested cut score of <26 may overpathologize neurologically intact individuals. Further research utilizing ROC curve analysis should be conducted to establish appropriate cutoff scores for various populations which may differ from the present sample.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it