A journey with no roadmap—The need for validated criteria of the MS prodrome
Bibliographic record
Abstract
BACKGROUND: A growing body of compelling evidence has emerged to validate a set of signs and symptoms that indicates the onset of disease before more typical signs and symptoms present to fulfill a diagnosis of MS. On 24 June 2021, a group of international researchers, patient advocates, and Society representatives led by Professors Helen Tremlett (University of British Columbia) and Ruth Ann Marrie (University of Manitoba) convened virtually for a workshop. OBJECTIVE: Identify key gaps in knowledge, opportunities, and research priorities regarding the prodromal stage of MS. METHODS: The group developed a new framework for MS that includes the stage of early signs and symptoms of MS-and outlined a roadmap to guide future research, with the "goal of preventing the progression to onset of typical symptoms of MS in those who present during the prodromal stage of MS". RESULTS: If high-risk individuals in the early stages of MS can be identified with a high degree of certainty, there is an opportunity to intervene and minimize the risk of progressing to typical MS symptoms and a diagnosis of MS. CONCLUSION: Standardized criteria must be developed, validated, and point of intervention found to better recognize, better diagnose, and better treat MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".