Collision tumor with diffuse large B cell lymphoma and gastric cancer
Bibliographic record
Abstract
A 71-year-old man started having headaches and sweating, and fainted twice. The following day, the patient was examined at our hospital's emergency room and a blood test showed he had a gastrointestinal hemorrhage. An esophagogastroduodenoscopy found a 20 mm ulcer with irregular edges in the upper part of the stomach body (Fig. 1), and a 30 mm depressed lesion accompanied by swelling in the area from the incisura angularis in the lesser curvature to the anterior wall (Fig. 2). The latter was hemorrhagic and oozing from the mucosa was also observed. A biopsy showed that the former was a poorly differentiated adenocarcinoma [Group 5, adenocarcinoma, gastric mucosa (por)] invading the submucosa, and the latter a poorly differentiated cancer [Group 5, adenocarcinoma, gastric mucosa (por > sig)] that accompanied the mixture in signet-ring cell carcinoma. A computed tomography scan revealed a 20 mm swelling of the lymph nodes in the stomach and the patient was diagnosed with stage 3A progressive stomach cancer. He requested surgery and received a total gastrectomy and cholecystectomy, returning home next month.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".