Diagnostic modalities for the evaluation of small bowel disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: This review summarizes the recent developments in the evaluation of small bowel disorders using videocapsule endoscopy (VCE) and serological and breath-test biomarkers. RECENT FINDINGS: The ability to visualize the small bowel was revolutionized with the introduction of VCE technology. VCE allows for accurate, noninvasive visualization of the small bowel mucosa. This device is invaluable in the investigation of obscure gastrointestinal bleeding (OGIB), occult bleeding with iron deficiency anaemia, small bowel Crohn's disease (CD), small bowel neoplasms and other mucosal disorders. Recent studies underscored the utility of VCE for documenting the extent and severity of small bowel CD as well as monitoring activity after therapy. The accuracy of the discrimination between small bowel tumours and benign bulges has been improved by a novel endoscopic algorithm. The accuracy of VCE was also evaluated as a potential noninvasive alternative to small bowel biopsies in suspected celiac disease. New findings have been made using breath tests and other biomarkers for the diagnosis of celiac disease, irritable bowel syndrome and bacterial overgrowth. SUMMARY: VCE as well as breath-test biomarkers play a major and expanding role in the diagnosis and monitoring of various small bowel disorders.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".