Mapping of Cognitive Pathways in Indian Ageing Population
Bibliographic record
Abstract
BACKGROUND: Cognitive Reserve(CR) a concept based on the brain plasticity, is a mechanism that delays or minimizes clinical manifestations of brain changes due to aging. Prospective epidemiologic studies non-demented individuals have shown that education, occupational duration and complexity, and greater lifetime engagement in cognitively stimulating activities are associated with a reduced risk of dementia. We study the cognitive reserve and its neuroimaging correlate. METHODS: Prospective cross-sectional study. 500 subjects were screened, Recruitment of subjects with inclusion criteria of age 40-80 yr without neurodegenerative or psychiatric disorder. Clinical History and presence of CVD risk factors were investigated. MMSE, MOCA, Selected neuropsychology tests were done to evaluate cognitive status, CR assessed by CRIq scale. Biochemical and MRI(volumetry) and DTI(FA, Diffusivity. RESULT: 252 pts were recruited, Mean age -53 yrs. 33% female. Diabetes(17%) and hypertension(24%). Mean MOCA score 24.CRIq was high in 10 subjects and majority had medium score. Significant association was found between Verbal and Category fluency with low CRIq and Serum ferritin with brain volume. Fractional isotropy(FA) values were reduced in central part of corpous callosum corelated with verbal fluency. CONCLUSION: Cognitive reserve can play a significant modifiable risk factor for cognitive decline. Neuroimaging can play an important biomarker to diagnose and in prognosis of cognitive impairment.
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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 | 0.002 | 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".