Gastric neuroendocrine carcinoma arising from heterotopic pancreatic tissue
Bibliographic record
Abstract
An 85 year old man presented with symptoms of dyspepsia and increase in stool frequency of two months duration. Upper endoscopy revealed an ulcer and the biopsy was interpreted as carcinoma with endocrine features. A formal distal gastrectomy was planned, but intraoperatively, because of the patient's condition, a wedge resection was performed. Histology revealed a neuroendocrine tumour (grade 1), located mainly in the submucosa, which had caused mucosal attenuation and ulceration. Associated with the tumour and at its periphery was heterotopic pancreatic tissue composed of acini, ducts, and endocrine cells. The tumour was strongly positive for chromogranin and focally for synaptophysin. There was no associated chronic atrophic gastritis or G cell hyperplasia. A discrete focus of high grade neuroendocrine carcinoma (grade 3) within the typical (grade 1) neuroendocrine tumour was also present. This case illustrates a grade 1 neuroendocrine carcinoma, with a small grade 3 focus, arising within or intimately associated with heterotopic pancreatic tissue in the stomach. Although the two entities may be separate, their close topographical association favours the possibility of neuroendocrine carcinoma arising from the heterotopic pancreas. Pathologists should be aware of the occurrence of pancreatic heterotopia in the stomach and the association of carcinoma with it.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".