Multiple sclerosis in First Nations Canadians: A pilot comparison study
Bibliographic record
Abstract
BACKGROUND: Genetic and clinical characteristics associated with multiple sclerosis (MS) may differ by ethnicity but few studies have evaluated whether characteristics of MS differ between individuals according to First Nations (FN) ethnicity. OBJECTIVE: Using a cross-sectional observational design, we compared clinical and genetic characteristics between people with MS of FN and non-FN ethnicity. METHODS: We recruited participants of FN ethnicity with MS. We conducted a medical records review for each participant followed by a standardized interview and drawing of blood samples. The blood underwent genetic analyses for several HLA alleles. We compared the study sample with 127 non-FN MS participants from another study conducted in the same region using the same data collection procedures. RESULTS: We included 144 participants with MS, of whom 17 (11.8%) self-identified as FN. The age of symptom onset was earlier and the diagnostic delay shorter among FN participants although these differences did not reach statistical significance. As compared to non-FN participants, FN participants with MS had increased odds of comorbid psychiatric disease (OR 5.38; 95% CI: 1.84-15.8), and were less likely to be HLA-DRB1*1501 positive (OR 0.32; 95% CI: 0.11-0.96). CONCLUSION: Genetic and clinical characteristics of MS differ among Canadians of FN and non-FN ethnicity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".