IMAGINE Network’s Mind And Gut Interactions Cohort (MAGIC) Study: a protocol for a prospective observational multicentre cohort study in inflammatory bowel disease and irritable bowel syndrome
Bibliographic record
Abstract
INTRODUCTION: Gut microbiome and diet may be important in irritable bowel syndrome (IBS), inflammatory bowel disease (IBD) and comorbid psychiatric conditions, but the mechanisms are unclear. We will create a large cohort of patients with IBS, IBD and healthy controls, and follow them over time, collecting dietary and mental health information and biological samples, to assess their gastrointestinal (GI) and psychological symptoms in association with their diet, gut microbiome and metabolome. METHODS AND ANALYSIS: This 5-year observational prospective cohort study is recruiting 8000 participants from 15 Canadian centres. Persons with IBS who are 13 years of age and older or IBD ≥5 years will be recruited. Healthy controls will be recruited from the general public and from friends or relatives of those with IBD or IBS who do not have GI symptoms. Participants answer surveys and provide blood, urine and stool samples annually. Surveys assess disease activity, quality of life, physical pain, lifestyle factors, psychological status and diet. The main outcomes evaluated will be the association between the diet, inflammatory, genetic, microbiome and metabolomic profiles in those with IBD and IBS compared with healthy controls using multivariate logistic regression. We will also compare these profiles in those with active versus quiescent disease and those with and without psychological comorbidity. ETHICS AND DISSEMINATION: NCT03131414.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".