Strategy for the Choice of Appropriate Mild Cognitive Impairment Screening Scales for Community-dwelling Older Adults
Bibliographic record
Abstract
With the deepening and acceleration of the aging process, an increasing prevalence of mild cognitive impairment (MCI) is found in China's elderly population. To reduce MCI prevalence in this group, early screening and diagnosis are approaches having great social significance. To provide support for the choice of appropriate tools for early screening and identifying MCI in community-dwelling Chinese older adults, we comprehensively reviewed the commonly used scales in clinical MCI screening and assessment〔Informant Questionnaire on Cognitive Decline in the Elderly Individuals (IQCODE) , Cambridge Neuropsychological Test Automated Battery, Montreal Cognitive Assessment, Clock Drawing Test, Clock Reading Test, Clock Setting Test, Consortium to Establish a Registry for Alzheimer's Disease, Ascertain Dementia 8 (AD8) , Addenbrooke's Cognitive Examination-Revised (ACE) , and General Practitioner Assessment of Cognition〕, and put forward a strategy after analyzing the advantages and disadvantages of each of the above-mentioned scales, namely, combined use of the quick and highly effective AD8, IQCODE, and the sensitive and comprehensive ACE, for these three scales may make up for each other's shortcomings when they are used together.
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".