Primary lateral sclerosis (PLS) functional rating scale: PLS‐specific clinimetric scale
Bibliographic record
Abstract
INTRODUCTION: Our research aim was to develop a novel clinimetric scale sensitive enough to detect disease progression in primary lateral sclerosis (PLS). METHODS: A prototype of the PLS Functional Rating Scale (PLSFRS) was generated. Seventy-seven participants with PLS were enrolled and evaluated at 21 sites that comprised the PLSFRS study group. Participants were assessed using the PLSFRS, Neuro-Quality of Life (QoL), Schwab-England Activities of Daily Living (ADL), and the Clinical Global Impression of Change scales. Participants completed telephone assessments at 12, 24, and 48 weeks after enrollment. RESULTS: The PLSFRS demonstrated internal consistency as well as intrarater, interrater, telephone test-retest reliability, and construct validity. Significant changes in disease progression were detected at 6 and 12 months; changes measured by the PLSFRS vs the ALSFRS-R were significantly higher. DISCUSSION: The PLSFRS is a valid tool to assess the natural history of PLS in a shorter study period.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".