Evaluation of the Tokyo Cognitive Assessment for Predicting Cognitive Impairment in Rehabilitation Users
Bibliographic record
Abstract
[Purpose] This study aimed to evaluation of the Tokyo cognitive assessment (Toca) for predicting cognitive impairment in rehabilitation users. [Method] The variables of age, BMI, educational background, Toca for 36 rehabilitation users and 22 healthy elder were assessed. We compared cognitive functions in rehabilitation users who need support and healthy elders. [Results] Of the Toca 1 to 11 trials, there was a significant difference other than 9, 10 rials. The Toca scores with 8 points higher were significantly higher in healthy elders than in rehabilitation users. The area under the receiver-operator curve (AUC) for predicting mild cognitive impairment (MCI) by the Toca was 0.874. Using a cut-off point of 19/20, the Toca demonstrated a sensitivity of 83.9% and a sensitivity of 85.0% in diagnosing MCI. [Conclusion] The Toca is a brief cognitive screening tool with high sensitivity and specificity for detecting MCI as currently conceptualized in rehabilitation users.
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How this classification was reachedexpand
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 | 0.013 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".