Celiac Disease: Against the Grain in Gastroenterology
Bibliographic record
Abstract
The incidence of celiac disease has risen quickly and has a worldwide distribution in Europe, North and South America, Asia, the Middle East and Africa. This is attributed in part to increased availability in screening but also to the fast-rising gluten consumption and perhaps unknown environmental factors. In daily practice, this means that more subclinical cases and very young and elderly patients are diagnosed. The pathogenesis of celiac disease is a T-cell driven process initiated by gluten, leading to increased intestinal permeability and villous atrophy. The process requires HLA genotypes DQ2, DQ8 or both. Additional non-HLA alleles have been identified in genome-wide association studies. Serological testing, followed by duodenal biopsies, are still required to confirm the diagnosis. Advances are in the making for novel biomarkers to monitor disease and for pharmacological support of celiac disease. Medical costs and patient-perceived disease burden remain high in celiac disease, which point to the need for ongoing research in drug development to improve quality of daily life. Drugs undergoing phase I and phase II clinical trials include intraluminal therapies and vaccines to restore immune tolerance. These therapies aim to reduce symptoms and mucosal injuries as adjunct therapies to a gluten-free diet.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 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".