Measuring Disability Progression with the Multiple Sclerosis Functional Composite
Bibliographic record
Abstract
The multiple sclerosis functional composite (MSFC) is a three-part quantitative objective measure of neurologic function, measuring leg (Timed 25-foot Walk [25FTW]), arm (Nine-hole Peg Test [9HPT]) and cognitive (Three-second Paced Auditory Serial Addition Test [PASAT3]) function. The MSFC was developed to be a more sensitive measure of disability than the expanded disability status scale (EDSS) and has excellent reliability. Validity is supported by moderately strong correlations with EDSS, brain atrophy and quality of life. Advantages of the MSFC include its continuous scale and inclusion of several disease dimensions. Limitations include practice effects, the lack of a visual function component, variations in reference populations and limited understanding of clinically relevant MSFC z-score changes. MSFC z-score change has been used as a secondary end-point in MS trials, but EDSS progression remains the primary disability outcome. A new approach to MSFC data involves defining MSFC progression as worsening in an MSFC component by 15–20% over three months. With further study, this could be used as a primary disability outcome in future clinical trials.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".