Bibliographic record
Abstract
Type 2 diabetes mellitus in children is an emotionally charged issue and an emerging public health problem. 1 2 Until recently most children with diabetes mellitus had type 1, one of the most common3 and increasingly prevalent4 chronic diseases in children. Increasingly, however, type 2 diabetes is being reported in children from the United States, Canada, Japan, Hong Kong, Australia, New Zealand, Libya, and Bangladesh.5 The prevalence of type 2 diabetes in children ranges from 4.1 per 1000 12-19 year olds in the US to 50.9 per 1000 15-19 year old Pima Indians of Arizona. 1 2 Between 8% and 45% of recently diagnosed cases of diabetes among children and adolescents in the United States is type 2, and the magnitude of this disease may be underestimated. 1 2 The prevalence of the disease is on the rise in North America, and its incidence almost doubled in Japan between 1976-80 and 1991-5—from 7.3 to 13.9 per 100 000 junior high school children.5 These trends coincide with the rising prevalence of overweight and physical …
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".