Clinicopathological Staging of Dynamics of Neurodegeneration and Neuronal Loss in Alzheimer Disease
Bibliographic record
Abstract
Clinical and neuropathological staging of Alzheimer disease (AD) neurodegeneration and neuronal loss dynamics is the baseline for identification of treatment targets and timing. The aim of this study of 14 brain regions in 25 subjects diagnosed with AD and 13 age-matched control subjects was to establish the pattern of neurodegeneration, and the severity and rate of neuronal loss in mild cognitive impairment/mild AD (Functional Assessment Staging [FAST] test 3-4), moderate to moderately severe AD (FAST 5-6), and severe AD (FAST 7). The study revealed (1) the most severe neuronal loss in FAST 3-4; (2) the highest rate of neuronal loss in FAST 5-6, to the "critical" point limiting further increase in neuronal loss; (3) progression of neurofibrillary degeneration, but decline of neuronal loss to a floor level in FAST 7; and (4) structure-specific rate of neuronal loss caused by neurofibrillary degeneration and a large pool of neuronal loss caused by other mechanisms. This study defines a range and speed of progression of AD pathology and functional decline that might potentially be prevented by the arrest of neuronal loss, both related and unrelated to neurofibrillary degeneration, during the 9-year duration of mild cognitive impairment/mild 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".