Bibliographic record
Abstract
A 74-year-old man was admitted to hospital with relatively severe pain in the lower abdomen, largely in the right iliac fossa. Over the preceding 2 weeks, he had noted intermittent but milder pain that had been accompanied by episodes of nausea and vomiting. An image from an abdominal computed tomography (CT) scan taken in the Emergency Department is shown in Figure 1. The image shows a target lesion (arrow) with marked thickening of the small bowel wall, an intraluminal soft-tissue density mass and an eccentrically placed fatty area that represents the intussusception and the intussuscepted mesentery. The appearance was consistent with ileal–ileal intussusception. At laparotomy, intussusception with gangrene was confirmed and a segment of ileum (34 cm) was resected. The resected segment contained approximately 60 submucosal lipomas measuring up to 3 cm in diameter (Fig. 2). His postoperative course was uneventful and he was asymptomatic after follow-up for 12 months. The first report of multiple gastrointestinal lipomas (lipomatosis) has been attributed to Dr Hellstrom in 1906. The disorder appears to be rare as only 20 additional cases have been reported in the medical literature. Some of these have been associated with diverticulosis of the small bowel. Patients with multiple lipomas have had a mean age at diagnosis of approximately 50 years with equal numbers of men and women. In contrast to solitary lipomas that are usually located in the colon, multiple lipomas are largely located in the small bowel, particularly the ileum. Symptoms at presentation range from intermittent abdominal pain to acute presentations with intussusception and small bowel obstruction. Barium follow-through X-rays have revealed multiple polyps but the differential diagnosis needs to include other polyposis syndromes such as the Peutz–Jegher’s syndrome, lymphoid hyperplasia, lymphomatous polyposis and Cronkhite–Canada syndrome. CT scans can also be helpful for the diagnosis of larger lipomas, particularly if there are multiple homogeneous masses of low-density (Hounsfield units between −80 and −120). Most symptomatic patients with multiple lipomas have been managed by surgical resection, as abnormalities have been located in the small bowel and the preoperative diagnosis has often been unclear.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".