Bibliographic record
Abstract
Prior studies have established that patients with inflammatory bowel disease (IBD), specifically those with extensive and long-standing ulcerative colitis (UC), have an increased risk of subsequent colorectal cancer. These studies of UC, however, have been based on data from tertiary care settings, primarily in the United States and the United Kingdom. Others, even from similar geographic areas in the US, have shown that the magnitude of this risk may not be so significant.1,2 In addition, others have argued that the risk of cancer is not increased in patients with colitis and data may be further influenced by an underlying baseline risk of colon cancer that is geographically or environmentally influenced, rather than related to IBD per se.3 In Crohn's disease (CD), precise cancer risk data are also not available. A number of studies, mainly from tertiary care centers in the US and the UK, have suggested that patients with CD have an increased risk of colorectal cancer,4,5 as well as an excess overall mortality attributed to digestive tract tumors, including small intestinal cancers.6 Weedon et al4 described colorectal cancer complicating the course of CD in 8 of 449 patients (or ≈1.2% for an estimated 20 times greater risk than that of a control population). Similarly, Gyde et al5 reported an ≈4-fold increased risk in patients with CD in the UK. Recent cohort and population-based studies from Canadian centers, where reports of malignant diseases are legally required,6,7 are also consistent with an increased intestinal cancer risk in CD. Moreover, both myeloid and lymphoid malignancies may occur in CD,7,8 in part, possibly related to treatment with immunosuppressive agents or biological agents (e.g., infliximab).9,10 Finally, carcinoid tumors at some intestinal sites may be increased in CD.11
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".