Diabetes Prevention Trial 1
Bibliographic record
Abstract
The Diabetes Prevention Trial Type 1 (DPT-1) has recruited relatives of patients with type 1 diabetes throughout the United States and Canada. Of the group screened before June 30, 2000, 71,148 initial screening samples of DPT-1 subjects were tested for GAD65 autoantibodies (GAA) and ICA512 (IA-2) autoantibodies (ICA512AA). Of 71,148 relatives screened, first-degree relatives (4.63%, n = 59,752) had a significantly higher prevalence of autoantibodies than did second-degree relatives (2.61%, n = 9,856) (P < 0.0001 for both autoantibodies). Among first-degree relatives, siblings (5.47%, n = 27,128) had a significantly higher prevalence of autoantibodies than did offspring (3.98%, n = 17,063) and parents (3.88%, n = 15,561) (P < 0.0001 for both autoantibodies). Among offspring, the offspring (n = 105) of both parents with diabetes had twice (8.57%) the prevalence of autoantibodies than did the offspring (n = 16,901) of a single diabetic parent (3.96%). Interestingly, the offspring (n = 8,777) of diabetic fathers had a significantly higher prevalence of autoantibodies than did the offspring (n = 8,124) of diabetic mothers, but only among those aged 10-30 years (P < 0.0001). We conclude that the prevalence of anti-islet cell autoantibodies is affected by multiple levels of relationship to the proband.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.054 | 0.010 |
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".