Neuropathologic Correlates of Magnetic Resonance Imaging in Multiple Sclerosis
Bibliographic record
Abstract
The advent of magnetic resonance imaging (MRI) has revolutionized concepts of the pathogenesis of multiple sclerosis (MS). Magnetic resonance imaging provides the ability to delineate the evolution of the disease process over time; captured static snapshots can then be used in pathologic correlations studies. Certain patterns in the 2- or 3-dimensional MRI sphere correlate very well with similar patterns of histopathology. A multimodality approach that makes use of numerous MRI techniques can lead to significant insights into the nature of the changes in the CNS. MRI-pathology correlation studies in MS are being performed using newer MRI techniques as they become available. Such correlations and basic histopathologic studies have shown abnormalities in MS far beyond the well-documented changes in the plaque and have brought into question the dogma that MS is an initially inflammatory nondegenerative disease. This review briefly outlines technical considerations in MRI-pathology correlative studies and describes the past and current status of our ability to correlate focal and diffuse changes on the MRI with neuropathologic findings in MS patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".