School attendance in children with Type 1 diabetes
Bibliographic record
Abstract
AIMS: To determine whether children with Type 1 diabetes mellitus (DM) miss more school than their non-DM siblings and peers and to identify factors associated with school absenteeism in children with DM. METHODS: School absenteeism data for the 2000-01 school year were obtained for 78 children with DM, 38 non-DM siblings and 118,269 age-matched peers in Toronto, Ontario. Questionnaires and hospital records were utilized to evaluate child-, family- and diabetes-related factors associated with school absenteeism in children with DM. RESULTS: Children with DM missed only slightly, albeit significantly more school than both their non-DM siblings (mean +/-sd: 10.9 +/- 8.9 vs. 8.1 +/- 8.1 days, P < 0.001) and peers (median: 8.8 vs. 5.5 days, P = 0.0005). A multiple regression analysis indicated that school absenteeism in children with DM was associated with their parents' attitudes towards school attendance (P = 0.002), poorer metabolic control (P = 0.006), shorter disease duration (P = 0.006) and a lack of aggressive behaviour (P = 0.02). CONCLUSIONS: With current management strategies, near normal school attendance is a reasonable goal for all children with DM and should be strongly encouraged by parents, educators and health care professionals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".