Comparison of Cognitive Functions Based on MMSE/MoCA-J Scores among Different Age Groups of Elderly Community Residents
Bibliographic record
Abstract
〔目的〕MMSE・MoCA-Jを使用し，高齢者における年代間の認知機能の違いについて比較検討した．〔対象と方法〕地域在住の高齢女性48名の認知機能をMMSE・MoCA-Jにて評価した．年齢を4群（75-79歳，80-84歳，85-89歳，90歳以上）に分類し，MMSEとMoCA-Jの総得点および下位項目得点を比較した．〔結果〕MMSE，MoCA-Jでは「計算」，MoCA-Jでは「Trail Making」において，加齢に伴う低下が認められた．〔結語〕高齢者の認知機能測定において，MMSEおよびMoCA-Jを使用し，下位項目を年代別に比較することで年代に応じた詳細な分析が可能となることが示唆された．
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".