Tumor-to-tumor metastasis: esophageal carcinoma metastatic to an intracranial paraganglioma
Bibliographic record
Abstract
Tumor-to-tumor metastasis (TTM) is a relatively rare but well-documented phenomenon. The authors report a unique case of esophageal carcinoma metastatic to an intracranial paraganglioma. A sellar and suprasellar tumor was found using MR imaging in an 81-year-old man who presented with a 3-week history of progressive headache and blurred vision. A subtotal excision of the tumor was achieved. Histopathological examination of the tumor disclosed a neoplasm with two distinct components: one showing the classic Zellballen pattern of a paraganglioma, the other exhibiting malignant features leading to the diagnosis of a poorly differentiated carcinoma metastatic to a sellar/suprasellar paraganglioma. The primary esophageal carcinoma was not uncovered until 2 months later, after the patient presented with upper gastrointestinal bleeding. The patient died 4 months after initial presentation. This case expands the spectrum of TTM, and emphasizes the importance of TTM in the practice of pathology.
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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 | 0.002 |
| 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 | 0.001 | 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".