The Impact of Inflammatory Bowel Disease in Canada 2018: A Scientific Report from the Canadian Gastro-Intestinal Epidemiology Consortium to Crohn’s and Colitis Canada
Bibliographic record
Abstract
Canada has among the highest rates of IBD in the world, and the number of people living with these disorders is growing rapidly. This has placed a high burden on the health care system and on the Canadian economy-a burden that is only expected to grow in the future. It is important to understand IBD and its impact on Canadian society in order to appropriately plan for health care expenditures, reduce the burden on patients and their families, and improve the quality of life for those afflicted with IBD. In Canada, there is a lack of public awareness of the impact of Crohn's disease and ulcerative colitis. Raising awareness is crucial to reducing the social stigma that is common with these diseases and to help individuals maximize their overall quality of life. A better public understanding of IBD can also help to raise and direct funds for research, which could lead to improved treatments and, ultimately, to a cure. This report from Canadian clinicians and researchers to Crohn's and Colitis Canada makes recommendations aimed at the public, policy-makers, scientific funding agencies, charitable foundations and patients regarding future directions for advocacy efforts and areas to emphasize for research spending. The report also identifies gaps in knowledge in the fields of clinical, health systems and epidemiological research.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".