The Japanese Study Group of Insulin Therapy for Childhood and Adolescent Diabetes (JSGIT): initial aims and impact of the family history of type 1 diabetes mellitus in Japanese children
Bibliographic record
Abstract
The Japanese Study Group of Insulin Therapy for Childhood and Adolescent Diabetes (JSGIT) was established in July 1994 with the chief aim to improve the quality of therapy for type 1 diabetes in children, an entity far less common in Japan than in Europe. We proposed four initial research topics: (i) to determine the current status of medical care and glycemic control in Japanese children with type 1 diabetes mellitus; (ii) to standardize the measurement of hemoglobin A1c; (iii) to establish a registry of a large cohort of patients in order to enable prospective studies to improve the quality of therapy for children with type 1 diabetes in Japan; and (iv) to enable participants of the JSGIT to hold a workshop twice annually. We registered a total of 736 patients from 45 hospitals throughout Japan. Intervention via insulin treatment was instituted after 2 yr for those patients whose hemoglobin A1c level was more than 8.1%. The proportion of patients receiving multiple insulin injections increased after intervention; however, average hemoglobin A1c in females remained significantly higher than in males. We identified two forms of diabetes in Japanese children: a rapidly progressive form and a more slowly progressive form. There was a significantly higher prevalence of a family history of diabetes in first-degree relatives in the slowly progressive form. These preliminary findings are the result of the first collaborative study of childhood diabetes in Japan.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".