Bibliographic record
Abstract
This thesis explores aspects pertinent to the phenotypic classification of paediatric patients with inflammatory bowel disease (IBD). In the current era it has never been more important to have rigourous phenotypic classification to facilitate genotype-phenotype correlation studies as well as to optimize design of clinical trials of emerging therapies, where frequently response may differ according to phenotype of disease.\nThe first study examined the reliability of the Montreal Classification for classifying paediatric IBD patients. This is the first study exploring the reliability of phenotypic classification in a paediatric population. The reliability of assigning an overall diagnosis of type of IBD was good, but not excellent. Amongst Crohn’s disease patients, reliability of assigning disease behaviour was excellent, while the reliability of assigning disease location categories varied from fair to good. The percentage agreement when describing disease extent for ulcerative colitis was high. \nThe second study described the evolution of disease phenotype in a cohort of paediatric IBD patients. Similar to observations in adult-onset IBD, disease location was found to be relatively stable, while Crohn’s disease behaviour evolves from an inflammatory to a stricturing and/or penetrating phenotype in 20% of patients by 5 years of follow-up.\nThe final study explored the association between 2 polymorphisms in the NOD2 gene with the requirement for intestinal resection (a surrogate marker of complicated disease) in models that included and excluded disease duration. Although no difference was found, this may have been influenced by data quality, which was suboptimal. \nIn conclusion, this thesis has demonstrated that imprecision exists in the phenotyping of paediatric IBD patients, in whom phenotypic characteristics evolve over time. It is pertinent that disease duration be considered in any study attempting to make phenotypic correlations.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".