P3–225: Quick and accessible: The highly correlated Cognitive Self‐Test (CST)
Bibliographic record
Abstract
The Cognitive Self Test (CST), formally the Computerized Self Test, is an interactive, internet-based instrument designed to assess functional cognitive domains impaired in Alzheimer's disease (AD) and mild cognitive impairment (MCI). The CST assesses six cognitive domains: verbal fluency, visuospatial, memory, attention, executive functions, and perceptual/processing speed in less than 10 minutes. This study aims to evaluate the correlation between the CST-score parameter, the CST-time parameter and a well established neurocognitive battery. Methods: We collected data from 35 subjects in three groups: 8 cognitively healthy normal controls, 16 subjects with MCI and 11 subjects with early Alzheimer's disease. All subjects were recruited from a memory clinic with the inclusion criteria being greater than the age of 50, MMSE score ≥ 23 and a GDS score ≤ 10. Subjects having a significant history of alcohol or drug abuse, psychiatric disease history or having a dementing illness other than Alzheimer's disease were excluded. All subjects completed the following battery of neurocognitive measures in the same visit: CST, FAQ (Functional Activities Questionnaire), GDS (Geriatric Depression Scale-30point), CDR (Clinical Dementia Rating Scale), ADAS-Cog (Alzheimer's Disease Assessment Scale, Cognitive Subscale), AVLT (Auditory Verbal Learning Test), BNT (Boston Naming Test, 30-item odd), Semantic Fluency-Animals and Vegetables, Clock Draw and Clock Copy, Trail A and B, MoCA (Montreal Cognitive Assessment) and MMSE (Mini- Mental Status Examination). Two individuals administered the neurocognitive assessment for all subjects. One individual administered only the CST, and the other individual administered the remainder of the neurocognitive assessment. The CST results were not disclosed to the non-CST administrator. Results: The CST-score parameter is significantly correlated to more neuropsychological tests than the CST-time parameter. The CST-score is significantly correlated 17 out of 21 possible correlations and the CST-time parameter is significantly correlated 9 out of 21 possible correlations, see Table 1 and Table 2. Conclusions: The CST-score parameter is a strong indicator of neuropsychological performance. Future studies are planned to evaluate the application of the CST-score in differentiating amongst cognitively healthy, MCI and early Alzheimer's diseased individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.053 | 0.021 |
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".