Bibliographic record
Abstract
BACKGROUND: Two genome scans for susceptibility loci for type 1 diabetes using large collections of families have recently been reported. Apart from strong linkage in both studies of the HLA region on chromosome 6p, clear consistent evidence for linkage was not observed at any other loci. One possible explanation for this is a high degree of locus heterogeneity in type 1 diabetes, and we hypothesised that the sex of affected offspring, age of diagnosis, and parental origin of shared alleles may be the bases of heterogeneity at some loci. METHODS: Using data from a genome wide linkage study of 356 affected sib pairs with type 1 diabetes, we performed linkage analyses using parental origin of shared alleles in subgroups based on (1) sex of affected sibs and (2) age of diagnosis. RESULTS: Among the results obtained, we observed that evidence for linkage to IDDM4 on chromosome 11q13 occurred predominantly from opposite sex, rather than same sex sib pairs. At a locus on chromosome 4q, evidence for linkage was observed in sibs where one was diagnosed above the age of 10 years and the other diagnosed below 10 years of age. CONCLUSIONS: We show that heterogeneity tests based on age of diagnosis, sex of affected subject, and parental origin of shared alleles may be helpful in reducing locus heterogeneity in type 1 diabetes. If repeated in other samples, these findings may assist in the mapping of susceptibility loci for type 1 diabetes. Similar analyses can be recommended in other complex diseases.
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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 | 0.003 |
| 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) | 0.003 | 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".