Bibliographic record
Abstract
Canada has one of the highest rates of childhoodonset inflammatory bowel disease (IBD) in the world, with the recent Crohn’s and Colitis Canada’s 2023 Impact of Inflammatory Bowel Disease in Canada Report demonstrating that approximately 6,158 children and youth under 18 years are living with IBD, along with 600-650 new diagnoses under age 16 per year. This number is expected to rise to 8,079 by 2035. This represents approximately 10-20% of newly diagnosed patients. Concerningly, although still relatively uncommon compared with adolescent onset IBD, the incidence has increased most significantly in children under 5 years old. Recent health administrative data demonstrated the national incidence of IBD, overall, to be 29.9 per 100,000 (95%CI: 28.3, 31.5) in 2023, with increasing incidence in pediatrics (AAPC:1.27%; 95%CI:0.82, 1.67), despite stable incidence in adults (AAPC:0.26%; 95%CI: -0.42, 0.82). Figure 1 demonstrates that this increase in pediatric incidence is a worldwide phenomenon. Current IBD care in pediatrics is moving toward a precision medicine approach, with unique and standardized approaches to genetics, risk stratification and disease phenotype, nutritional and advanced therapies, and specialized multidisciplinary clinics with knowledge of the unique challenges pediatric patients and their families face with a diagnosis of IBD.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".