The changing epidemiology of paediatric inflammatory bowel disease: authors’ reply
Bibliographic record
Abstract
Sirs, We thank Henderson et al.1 for their comments on our article.2 We did not use the age-limits proposed in the Montreal or Paris classifications because this study was not specifically devoted to paediatric Crohn’s disease (CD). Our aim was to look at the temporal variation in CD incidence in the whole population living within Northern France. The population was therefore stratified by 10-year age groups as previously described.3, 4 As far as disease location, we agree that the classification of ileal lesions with caecal involvement as L3 may have led to an overestimation of the number of cases of L3 disease when compared with other studies. Nevertheless, as this classification was applied during the whole study period, it did not influence the increase in extensive disease we reported. It is a matter of fact that the percentage of successful ileal intubations has increased from 13% in 1988–1990 to 55% in 2006–2007. This explains in part the 10% increase in complete bowel investigation during the study period. We actually identified only 10 cases of isolated L4 disease which is lower than in other studies. Results are difficult to compare because it is often not clear what percentage of patients underwent full bowel examination in other studies. Finally we are also collecting unclassified IBD (IBDU) in EPIMAD Registry. These patients represent 5% of all IBD cases, a percentage that has remained stable since 1988. We agree that the overall incidence of IBD including IBDU may thus be even higher.3–5 In conclusion, we believe that the different points raised by Henderson et al.1 do not alter the conclusions of our article. Declaration of personal and funding interests: None.
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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 | 0.007 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.019 | 0.026 |
| Insufficient payload (model declined to judge) | 0.005 | 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".