Bibliographic record
Abstract
Recent case-series studies and smaller cross-sectional samples have reported alarming observations among youth: once a disease of middle age and older adulthood, type 2 diabetes now represents nearly one-half of newly diagnosed diabetes cases in some obese adolescent African-American and Hispanic populations (1). Furthermore, the metabolic syndrome, also known as syndrome X or the insulin resistance syndrome, has recently been documented in youth (2). The cornerstone of this syndrome is obesity and insulin resistance, giving rise to a plethora of risk factors for type 2 diabetes and cardiovascular disease, including impaired glucose tolerance, dyslipidemia, hypertension, impaired fibrinolytic activity, and a heightened state of systemic inflammation (3). In this issue of the journal, Allard et al. (4) describe fasting blood concentrations of glucose, insulin, and free fatty acids (FFAs) in children and adolescents. These timely data, from a carefully conducted population-based study in Quebec, Canada, contribute to our understanding of the potential public health impact of the pediatric obesity epidemic. As expected for a typical population of youth, the distribution of fasting glucose was quite narrow, whereas that of fasting insulin was quite broad. The difference between the 5th and 95th percentiles for fasting insulin (∼390%) was ∼15 times greater than that of fasting glucose (∼25%). Concentrations of fasting glucose were somewhat higher for boys than for girls, whereas fasting insulin concentrations were somewhat higher for girls than for boys. As such, the homeostasis model of insulin resistance (HOMA), the product of glucose and insulin, was comparable between the genders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".