Subjective Cognitive Decline in Preclinical Alzheimer's Disease
Bibliographic record
Abstract
Older adults with subjective cognitive decline (SCD) in the absence of objective neuropsychological dysfunction are increasingly viewed as at risk for non-normative cognitive decline and eventual progression to Alzheimer's disease (AD) dementia. The past decade has witnessed tremendous growth in research on SCD, which may reflect the recognition of SCD as the earliest symptomatic manifestation of AD. Yet methodological challenges associated with establishing common assessment and classification procedures hamper the construct. This article reviews essential features of SCD associated with preclinical AD and current measurement approaches, highlighting challenges in harmonizing study findings across settings. We consider the relation of SCD to important variables and outcomes (e.g., AD biomarkers, clinical progression). We also examine the role of self- and informant-reports in SCD and various psychological, medical, and demographic factors that influence the self-report of cognition. We conclude with a discussion of intervention strategies for SCD, ethical considerations, and future research priorities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".