An Extremely Rare Case of Primary Malignant Melanoma of the Kidney
Bibliographic record
Abstract
Malignant melanoma (MM) is a tumor that usually occurs in the skin, but this malignant tumor can also develop in extracutaneous tissues, including urogenital tissues. In regard to MM occurring in urogenital tissues, bladder origin is common but renal primary MM is extremely rare. In the Department of Emergency and Urology at Gifu Municipal Hospital, a tumor of the right kidney was detected in a computed tomography scan to determine the cause of severe pain in the lower extremities of a 45-year-old Japanese woman. With the clinical diagnosis of renal cell carcinoma, resection of the right kidney was performed under laparoscopy. The cut surface of the tumor encapsulated by a thick fibrous capsule was dark brown, and the tumor cells with large nuclei, large nucleoli, acidophil cytoplasm, and numerous melanin granules showed papillary, solid, or alveolar growth. Immunohistochemically, the tumor cells were positive for Melan A and human melanoma black 45 (HMG45) but negative for transcription factor E3 (TFE3), transcription factor EB (TFEB), cytokeratin 7 (CK7), carbonic anhydrase 9 (CA9), and AEl/AE3. We conducted careful and detailed examinations, including an association of the patient's medical history, but there were no indications for tumors, particularly MM, in any organs. Therefore, she was ultimately diagnosed with primary kidney MM.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".