Cognitive function among physically independent very old people in an urban community in Japan: The Itabashi Oldest-Old Study II
Bibliographic record
Abstract
This study was conducted to clarify the characteristics of cognitive function among physically independent very old people dwelling in an urban community in Japan. Five hundred and thirteen Old-Old (aged 75-84 years) and 168 Oldest-Old (aged 85-100 years) adults participated. We carried out the Mini-Mental State Examination (MMSE) for measuring cognitive functions in the elderly. Age-related differences in the total score and sub-scale scores of the MMSE were analyzed by sex using ANCOVA, controlling for education, vision and hearing problems. Mean MMSE scores for Old-Old and Oldest-Old males were 27.53 and 25.88, respectively, and those for Old-Old and Oldest-Old females were 27.77 and 24.98, respectively. Age-related differences in the MMSE total score between the Old-Old and Oldest-Old were observed in both sexes, suggesting that overall cognitive functions continue to decline over time in very old age. Age-related differences between the Old-Old and Oldest-Old in items measuring, registration, calculation and delayed recall were observed in both sexes, and in addition, time orientation, place orientation, delayed recognition, writing sentences, and copying figures were observed in females. These findings suggest that the faculties are those most sensitive to normal aging among very old individuals. There were no age group differences in five items: reverse spelling, naming objects, repeating a sentence, listening and obeying, and reading and obeying.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".