A six‐fold gradient in the incidence of type 1 diabetes at the eastern border of Finland
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Type 1 diabetes results from gene-environment interactions in subjects with genetic susceptibility to the disease. We assessed the contribution of environmental and genetic factors to type 1 diabetes by comparing the incidence in two neighboring populations living in conspicuously different socioeconomic circumstances. RESEARCH DESIGN AND METHODS: We compared the incidence over a 10-year period (1990-99) in children younger than 15 years of age living in the Karelian Republic of Russia and in Finland. The frequency of susceptible and protective human leukocyte antigen (HLA)-DQ alleles was analyzed in 400 non-diabetic schoolchildren from Russian Karelia and 1000 Finnish subjects. RESULTS: The average annual age-adjusted incidence of type 1 diabetes was lower in Russian Karelia than in Finland: 7.4 per 100000 (95% confidence interval 3.5-11.3) versus 41.4 per 100000 (37.3-45.5), while there were no differences in the frequency of the HLA DQ genotypes predisposing to type 1 diabetes in the background populations. The incidence rate did not differ significantly between different ethnic groups in Russian Karelia (Finns/Karelians, Russians, others). CONCLUSIONS: There is a close to six-fold gradient in the incidence of type 1 diabetes between Russian Karelia and Finland, although the predisposing HLA DQ genotypes are equally frequent in the two populations. This suggests that environmental factors contribute to this steep difference in the incidence rate between these adjacent regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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