Season of birth is associated with multiple sclerosis and disease severity
Bibliographic record
Abstract
BACKGROUND: The latitude gradient in multiple sclerosis incidence indicates that low sun exposure and therefore vitamin D deficiency is associated with multiple sclerosis risk. OBJECTIVE: Investigation of the effect of month of birth, which influences postnatal vitamin D levels, on multiple sclerosis risk and severity in Sweden. METHODS: Patients and population-based controls were included from three nationwide cohorts. Differences in month of birth between cases and controls were analyzed using logistic regression and examined for effect modification by calendar year and geographic region at birth. RESULTS: Males had a reduced risk of multiple sclerosis if born in the winter and increased risk if born in the early fall. Individuals born before 1960 had an increased risk if born in summer or fall. Being born in late summer and early fall was associated with more severe disease. CONCLUSIONS: We identified a birth cohort effect on the association between the month of birth and multiple sclerosis, with a more significant effects for births before 1960. This coincides with a period of lower breastfeeding rates, recommended intake of vitamin D, and sun exposure, resulting in a lower vitamin D exposure during the fall/winter season for infants born in the summer.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".