Incorporating New Diagnostic Schemas, Genetics, and Proteinopathy into the Evaluation of Frontotemporal Degeneration
Bibliographic record
Abstract
PURPOSE OF REVIEW: Within the continuously growing body of knowledge in the field of dementia, frontotemporal degeneration stands out in importance as the second most common cause of early-onset dementia after Alzheimer disease. Neurologists, neuropsychologists, and speech pathologists are particularly involved in the diagnosis and recognition of etiologies for patients with deficits in frontal lobe function and language. RECENT FINDINGS: The recent discovery of a novel mutant gene (C9ORF72) and the new nomenclature adopted for subclassification have significantly promoted our understanding of this disorder. SUMMARY: This article relates the most recent consensus criteria for diagnosis of the two forms of frontotemporal degeneration (ie, behavioral and primary progressive aphasia variants) to basic neurologic principles and remind clinicians of the neuropsychiatric and neuroradiologic components that clarify frontotemporal degeneration diagnoses and guide management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".