P3–052: Brains for Dementia Research: MMSE profile of the living cohort
Bibliographic record
Abstract
Brains for Dementia Research (BDR) is a network of six UK brain banks/collection centres that aims to address the shortage of high-quality post-mortem brains from people with dementia and suitable control cases and provide researchers with detailed clinical information on each case. Post-mortem brains are critical to our understanding of neurodegenerative processes in dementia and the underlying causes of the symptoms observed. With increasing research sophistication two things are clear: (1) the value of relating clinical information obtained during life to post-mortem biochemistry, and (2) genetic association studies require large numbers of samples from clinically, histopathologically and biochemically characterised tissue. Since BDR began in 2008 nearly 1,800 people in the UK have signed up to take part in regular assessments and agreed to donate their brain. For those with a diagnosis of dementia the following tests of memory, noncognitive behavior, mood and function will be undertaken: Mini Mental State Examination, Montreal Cognitive Assessment (MoCA), Alzheimer's Disease Assessment Scale Cognitive subscale (ADAS-Cog), Clinical Dementia Rating, Neuropsychiatric Inventory, Bristol Activities of Daily Living Scale, Cornell/Geriatric Depression Scale, Hachinski Ischaemic Scoring System Sensory/Motor Impairment. For controls, the same panel of tests will be used with the option of employing the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) cognitive battery. These tests will berepeated annually for those with a diagnosis of dementia, while the frequencyfor those without dementia will every 2 to 5 years. The average age of the living cohort is 76 made up of 547 males and 986 females. Approximately 21% (329) have a diagnosis of dementia. 55% of the cohort had MMSE values obtained in the last 3 years. The distribution of MMSE scores is shown in Figure 1.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.003 |
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".