Differentiating the Dementias. Revisiting Synucleinopathies and Tauopathies
Bibliographic record
Abstract
Dementia is a common, chronic and progressive illness. Many different types of dementia exist. It is important to have knowledge of the various dementia presentations so that the clinician can differentiate one type from another. Past and current approaches of classifying dementias are reviewed in this paper. The past cortical/subcortical scheme is reviewed as well as the current synucleinopathy/tauopathy scheme. This paper focuses on the most common synucleinopathies and tauopathies including Alzheimer's Dementia, Dementia with Lewy Bodies, Parkinson's Disease, Frontotemporal Dementia, Progressive Supranuclear Palsy, Multiple System Atrophy and Corticobasal Ganglionic Degeneration. We systematically approach each dementia and review cognitive, psychiatry and neurological features of each. We also compare and contrast each dementia and the synucleinopathies and taupoathies alike. Our goal is to provide the clinician with sufficient knowledge to competently and confidently diagnose a patient who presents with progressive cognitive decline and deterioration in functioning.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".