Monthly Ambient Sunlight, Infections and Relapse Rates in Multiple Sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Monthly variation in multiple sclerosis (MS) relapses has been found. The relationship between seasonal environmental factors, infections, serum vitamin D [25(OH)D] and MS relapses is undetermined. METHODS: We prospectively followed a population-based cohort of relapsing-remitting (RR) MS patients in Southern Tasmania for a mean 2.3 years (January 2002-April 2005). Associations between monthly ambient environmental factors, estimated serum 25(OH)D, upper respiratory tract (URT) infections and relapse rates were examined using weighted Pearson's correlation and linear regression. RESULTS: Of 199 definite MS patients, 142 had RRMS. The lowest relapse rate of 0.5 per 1,000 days (95% CI: 0.2-1.3) occurred in February (mid-late summer) versus the March-January RR of 1.1 per 1,000 days (95% CI: 0.9-1.3; p = 0.018, weighted regression). Monthly relapse rates correlated with: (1) prior erythemal ultraviolet radiation (EUV): lagged 1.5 months, r = -0.32, p = 0.046; (2) URT infection rate: no lag, r = 0.39, p = 0.014; (3) 25(OH)D: no lag, r = -0.31, p = 0.057. The association between URT infections and relapses was reduced after adjustment for monthly EUV. CONCLUSIONS: Relapse rates were inversely associated with EUV and serum 25(OH)D levels and positively associated with URT infections. The demonstrated lag between EUV but not 25(OH)D and relapse rates is consistent with a role for EUV-generated 25(OH)D in the alteration of relapse rates. Future work on the association between URT infections and relapses should be considered in the context of ultraviolet radiation and vitamin D.
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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 | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it