Educational level and its Association with the domains of Japanese version of the Montreal Cognitive Assessment Test
Bibliographic record
Abstract
The Montreal Cognitive Assessment （MoCA） は軽度認知障害のスクリーニング検査であり，合計得点の算出時に教育年数を考慮する特徴がある。先行研究では，MoCAの下位指標の一つである言語領域得点において教育年数の影響が報告されているが，日本においてMoCAの各認知領域得点と教育年数との関連は明らかになっていない。そこで本研究では，教育年数がMoCAの各認知領域に与える影響を評価するため，60歳以上の健常高齢者104名に対し日本語版MoCAおよび教育年数の聴取を行い，教育年数で2群（低群：12年以下，37名；高群：13年以上，67名）に分け，各認知領域得点についてWelch’s t-testを行った。その結果，先行研究で報告されている言語領域得点（t（76.0）＝－2.114, p＝0.038）に加え，注意領域得点（t（62.8）＝－2.075, p＝0.042）においても，教育年数高群の方が低群よりも有意に高かった。以上より，日本では教育年数がMoCAの言語領域だけでなく注意領域にも影響を与えることが示唆された。
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".