Relationship between the incidence of type 1 diabetes and enterovirus infections in different European populations: Results from the EPIVIR project
Bibliographic record
Abstract
The incidence of type 1 diabetes varies markedly between countries. As enterovirus infections have been linked to type 1 diabetes, we determined whether this variation correlates with the frequency of enterovirus infections in different Caucasian populations in Europe. Enterovirus antibodies were examined in the background population (1-year-old and 10-14-year-old children) in seven countries with either exceptionally high (Finland and Sweden) or low/intermediate incidence of diabetes (Estonia, Germany, Hungary, Lithuania, Russia) using EIA and neutralisation assays. Enterovirus antibodies were less frequent in countries with high diabetes incidence compared to countries with low diabetes incidence (P<0.001). This suggests that enterovirus infections are not particularly common in countries with high diabetes incidence. In contrast, there seems to be an inverse correlation between the incidence of type 1 diabetes and enterovirus infections in the background population, which is in line with the previously proposed polio hypothesis according to which the complications of enterovirus infections become more common in an environment with a decreased rate of infections.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".