Bibliographic record
Abstract
Objective To investage the cognitive function of the eldly in an urban community in Beijing and explore its risk factors.Methods Totally 129 elderly individuals aged 80 years or above in Dayou Beili,an urban community in Beijing,were enrolled in this study.Initially,the subjects were evaluated by Mini Mental State Examination(MMSE)and Montreal Cognitive Assessment(MoCA).Subjects with an MMSE score ≤24 or MoCA≤15 were further screened by Activity of Daily Living Scale(ADL) and diagnosed as vascular dementia or Parkinson disease with dementia according to DSM-Ⅳ and NINDS-AIREN.Results The average MoCA score of these 129 subjects was 22.82,and the average MMSE score was 26.45.Twelve subjects were newly diagnosed as dementia,with a morbidity of 9.3%.Another 12 subjects had a past history of dementia.Aging and drinking were the independent risk factors for senile dementia,while high educational degree was a protective factor.The morbidity of dementia in the patients suffered from atrial fibrillation,alcohol addiction,Parkinson′s disease,smoking,stroke,coronary heart disease,diabetes mellitus,hypertension,and dyslipidemia was 36.84%(7/19),30.77%(8/26),28.57%(2/7),22.22%(12/54),20.00%(15/75),19.57%(9/46),16.22.00%(6/37),15.09%(16/106),14.04%(8/57),respectively.Conclusion The cognitive function of the eldly in Dayou Beili community is in relatively good shape.Meanwhile,it is important to prevent senile dementia through smoking cessation,stopping harmful alcohol use and adopting early treatment for patients with cardiac cerebral vascular diseases and Parkinson′s disease.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".