Gross Anatomy of the Corpus Callosum in Alzheimer’s Disease: Regions of Degeneration and Their Neuropsychological Correlates
Bibliographic record
Abstract
BACKGROUND/AIMS: Differences in the gross shape of the corpus callosum (CC) and its subregional areas were investigated on brain MRI of patients with probable Alzheimer's disease (AD) and age- and gender-matched healthy normal control subjects. The AD patients differed from the normal control subjects in terms of a more convex shape and a reduced area of the CC. METHODS: As for the comparisons of the subregional areas of the CC, we adapted a splitting method which takes into account the modification of the global shape of the CC, and we implemented it by normalizing the CC, to avoid the bias introduced by the observed callosal shape variability. RESULTS: The application of this method unveiled that the regional CC reductions were located in the anterior and posterior third of the CC, i.e. where small myelinated fibers are more frequent. None of the neuropsychological scores collected at the time of the MRI investigation of AD could predict a regional and/or overall callosal area reduction. The only measure that correlated with area of the isthmus of the CC was the MMSE that was administered to all participants. CONCLUSIONS: This latter result may be used as an in vivo indicator of the progress of neocortical disintegration in AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".