Prediction of transition from cognitive impairment to senile dementia: a prospective, longitudinal study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this investigation was to replicate the statistical approach used in a previous investigation (Toronto study) within a French population to determine the best predictive model for Alzheimer's disease (AD). METHOD: Data from neuropsychological tests from two prospective studies were entered into a regression model. RESULTS: Replication of the statistical approach in the Montpellier sample produced a three-test model with a specificity of 99% and sensitivity of 73%. This model consisted of a delayed auditory verbal recall test, a construction test, a category fluency test and provides probability estimates for the transition to dementia in individual cases. CONCLUSION: The models derived from these two longitudinal studies provide an empirical basis for the selection of tests for the definition of mild cognitive impairment of the Alzheimer type (MCI-A). The small set of tests derived are suitable for use in general practice.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it