Interrelationships among body composition, nutrient intake, physical activity, medical management and glycemic control in children with type 1 diabetes
Bibliographic record
Abstract
'Objective'. To investigate if children with type 1 diabetes, compared to those without, had higher weight for height, higher fat mass, and/or a more central fat distribution, and to examine the relationship of these variables with age, nutrient intake, physical activity, medical management and glycemic control. 'Study design'. Females (n = 27) and males (n = 24) with type 1 diabetes, were compared to control females (n = 34), and males (n = 34), between the ages of 8 and 17 years, for weight, height, body mass index (BMI), percent total and regional body fat in a cross-sectional design. Weight and height were corrected to age by calculating Z-scores using the 1977 National Centre for Health Statistics data set; Body Mass Index (BMI) was calculated as kg/m2 and as Z-scores using data complied by Rosner et al (1998). Nutrient Intake was assessed using one 24 hour recall interview and one 3 day food record. Physical activity was determined using a questionnaire and clinical information for children with diabetes was taken from the medical chart. Relationships among body composition, nutrient intake, physical activity, medical management and glycemic control were examined with correlation and linear regression. (Abstract shortened by UMI.)
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".