Bibliographic record
Abstract
During the past 20 years, results of several major trials have demonstrated that intensive management of type 1 and type 2 diabetes can delay or prevent the onset and progression of many complications of the disease.1–3 It is also clear from such studies that achieving good glycemic control requires mastering complex self-management skills and behaviors. In children and adolescents, mastery of such skills is often compromised by normal development. In adolescence, metabolic control tends to deteriorate as a result of the hormonal changes of adolescence associated with insulin resistance4 and adolescent autonomy associated with lower adherence to the treatment regimen.5 Adolescence is marked by rapid biological, physical, cognitive, emotional, and social changes.6,7 Adolescents engage in experimentation and risk-taking behaviors that may adversely affect self-care and clinical outcomes.8 Previous studies have led to the conclusion that the period of adolescence is often associated with neglect of self-monitoring, nutrition therapy recommendations, and pharmacological treatments.9,10 Such neglect in self-management is usually not associated with a deficit in knowledge; rather, the cognitive and developmental characteristics of adolescence make appropriate decision making more complex.11 Developmentally, adolescence is a time for identity formation and separation of self from families.12 The shift from parental support to peer support is normal during adolescence. However, it can place adolescents at increased risk for poorer diabetes and psychological adaptation. Development of relationships with peers is complicated for adolescents who have type 1 diabetes or are at risk for type 2 diabetes. Early adolescents want to be seen as the same as their peers and not to be treated differently. There is a strong fear of non-acceptance by the peer group and exclusion from peer activities that may make adolescents reluctant to disclose their diagnosis.13 This …
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".