A Survey of risk for developing dementia in community dwelling elderly in Chiang Mai and Lampoon
Bibliographic record
Abstract
Background: With increasing number of elderly people in Thailand, the number of elderly at risk of dementia is increased accordingly. Prevalence of dementia for those living in community is needed information for health promotion and prevention of dementia. Objectives: To investigate prevalence of dementia in elderly community dwellers living in Chiang Mai and Lampoon. Materisls and methods: Montreal Cognitive Assessment (MoCA), Thai version was used as a tool. Five communities including Maekha, San Kamphaeng, Sanklang, Nong Kaeo, Nong Khwai and Ma Kok were explored. One hundred and seventy six elderly persons participated in the study. Results: It was shown that 95.4% of participants were at risk for dementia. The prevalence reported from Maekha, Sanklang and Nong Kaeo were 97.7&, 96.7&% and 91.9%, respectively where Nong Khwai and Ma Kok were similar of 95.2%. Conclusion: All in all, there is a high prevalence of dementia in these community
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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 | 0.000 | 0.000 |
| 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".