Including Persistency of Impairment in Mild Cognitive Impairment Classification Enhances Prediction of 5-Year Decline
Bibliographic record
Abstract
Although older adults with Mild Cognitive Impairment (MCI) show elevated rates of conversion to dementia as a group, heterogeneity of outcomes is common at the individual level. Using data from a prospective 5-year longitudinal investigation of cognitive change in healthy older adults (N = 262, aged 64-92 years), this study addressed limitations in contemporary MCI identification procedures which rely on single occasion assessment ("Single-Assessment [SA] MCI") by evaluating an alternate operational definition of MCI requiring evidence of persistent cognitive impairment over multiple-testing sessions ("Multiple-Assessment [MA] MCI"). As hypothesized, prevalence of SA-MCI exceeded that of MA-MCI. Further, the MA-MCI groups showed lower baseline cognitive and functional performance and steeper cognitive decline compared with Control and SA-MCI group. Results are discussed with reference to retest effects and clinical implications.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".