Association of Cortical Atrophy Patterns With Clinical Phenotypes and Histopathological Findings in Patients With Rasmussen Syndrome
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Automated MRI analyses have identified variable patterns of cortical atrophy in Rasmussen syndrome. In this study, we aim to identify imaging phenotypes of Rasmussen syndrome, to clinically characterize these phenotypes, and to validate this imaging-based approach through histopathologic analysis. METHODS: -means clustering. Neuropsychological test results and results from neuropathologic analyses of biopsies were ascertained, and correlations between subtype-specific atrophy maps and normative maps (enhancing neuro imaging genetics through meta analysis [ENIGMA] and neuromaps toolbox) were used to characterize atrophy profiles and epicenter susceptibility. RESULTS: = 0.04). DISCUSSION: Using Rasmussen syndrome as a model, we validate imaging-based mapping of individual disease epicenters with histopathologic evidence. With further validation, network-based mapping of individual disease epicenters could potentially be used in Rasmussen syndrome to guide biopsy site selection, inform treatment decisions, and improve outcome prognoses.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".