P.070 Characteristics of patients presenting to a multiple sclerosis clinic in Hamilton, Ontario
Bibliographic record
Abstract
Background: Multiple sclerosis (MS) is a neurological disease which is highly prevalent in Canada. To date limited data exists on the characteristics of this population in Ontario. Methods: A retrospective chart review was conducted of initial patient presentations to a MS clinic in 2011. Initial and follow-up consult notes were reviewed. Patients with a previous MS diagnosis were excluded. Results: 81 patients presented to the clinic for the first time in 2011. 41 were given alternative diagnoses (non-MS). Of the remaining 40 patients (MS group), 9 had clinically or radiologically isolated syndrome and 8 were in a progressive phase of MS. The mean age of presentation was 22 (MS group) and 47 (non-MS group). The most common initial symptom in both groups was a sensory disturbance. The mean initial EDSS in the MS group was 1.75 (0-6.5). In the MS group only 35% were put on disease modifying treatments. The most common reasons for exclusion of treatment were progressive disease phase, clinically or radiologically isolated syndrome, and unclear diagnosis. In the non-MS group, the most common diagnoses were non-specific MRI findings, transverse myelitis and peripheral nerve or muscular diagnoses. Conclusions: This retrospective review has outlined the characteristics of a MS population in Ontario.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".