[A case of malignant melanoma from the esophagus responding to weekly paclitaxel therapy].
Bibliographic record
Abstract
A 44-year-old man had a tumor in the lower thoracic esophagus at a health check, and was initially diagnosed as an undifferentiated carcinoma of the esophagus by the esophago-gastric endoscope. Although curative chemoradiotherapy was scheduled after the diagnosis, the interim evaluation revealed that the tumor was malignant melanoma of the esophagus with right renal metastasis. Since then, CVD (cisplatin, vindesine and dacarbazine) therapy, palliative radiotherapy and DAC-Tam (dacarbazine, nimustine, cisplatin and tamoxifen) therapy were carried out, but all of them proved ineffective, and multiple newly metastatic lesions appeared in liver and lymph nodes. Oral intake was impossible because of progressing stricture of the esophagus. As a fourth-line therapy, weekly paclitaxel therapy was started, and his oral intake was improved after the second course. He received the therapy as an outpatient for four months. After the third course, tumor lesions were evaluated as a partial response by CT. Consequently, five courses of the therapy were performed with modest adverse effects. Weekly paclitaxel therapy was reasonably safe as reported in other reports and considered to be a promising regimen for malignant melanoma of the esophagus.
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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) | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".