Beyond <i>Helicobacter</i>: dealing with other variants of gastritis—an algorithmic approach
Bibliographic record
Abstract
In daily practice, the presence of inflammation in gastric biopsies prompts a mental algorithm, an early question being whether the lesion present is Helicobacter-associated. If Helicobacter organisms are not found, then there is a further algorithm, governed by the predominant type of inflammatory cells present, and the presence of other features such as intraepithelial lymphocytosis, a subepithelial collagen band, granulomas, coexisting chronic inflammation, focality, and superimposed reactive changes including erosions and ulcers. Each of these generates its own differential diagnosis. If no inflammation is present, then the two major changes specifically looked for are the changes associated with hypergastrinaemia, by far the most common cause of which is treatment with proton pump inhibitors, and reactive changes. These may be present with and without accompanying inflammation, and, when the epithelial changes dominate, the term gastropathy is preferred. In this article, we present an approach to non-Helicobacter inflammation and gastropathies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".