Single- and Multiple-Domain Amnestic Mild Cognitive Impairment: Two Sides of the Same Coin
Bibliographic record
Abstract
BACKGROUND: Amnestic mild cognitive impairment (aMCI) is considered a transition stage between normal aging and Alzheimer's disease (AD). Two main clinical subtypes of aMCI have been identified: (1) single-domain aMCI (aMCI-SD), with isolated episodic memory impairments, and (2) multiple-domain aMCI (aMCI-MD), with episodic memory impairments and deficits in one or more other cognitive domains. AIMS: To map the pattern of gray matter (GM) atrophy associated with aMCI-SD, aMCI-MD and mild AD. METHODS: A group of aMCI-SD, aMCI-MD characterized by executive function disorders, mild AD and cognitively unimpaired subjects underwent a comprehensive neuropsychological assessment and a high-definition MR brain scan. Voxel-based morphometry analysis was used to characterize the GM tissue loss in each patient group, and the common pattern of GM atrophy in aMCI-SD and aMCI-MD. RESULTS: aMCI-SD and aMCI-MD are characterized by a common pattern of GM atrophy within the medial temporal cortex, predisposing to AD and correlating with the severity of verbal memory symptoms. Moreover, the pattern of GM atrophy observed in aMCI-SD, aMCI-MD and mild AD revealed that, from an anatomical point of view, these three clinical syndromes could represent three severity points along the continuum between normal aging and AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".