Transplant Oncology in Primary and Metastatic Liver Tumors
Bibliographic record
Abstract
Transplant oncology defines any application of transplant medicine and surgery aimed at improving cancer patients' survival and/or quality of life. In practice, liver transplantation for selected hepato-biliary cancers is the only solid organ transplant with demonstrated efficacy in curing cancer. Four are the proposed future contributions of transplant oncology in hepato-biliary cancer (4-e). (1) evolutionary approach to cancer care that includes liver transplantation; (2) elucidation of self and non-self recognition systems, by linking tumor and transplant immunology; (3) exploration of innovative endpoints both in clinical and experimental settings taking advantage from the access to the entire liver explant; (4) extension of surgical limitation in the multidisciplinary approach to hepato-biliary oncology. The aim of this review is to define the principles of transplant oncology that may be applied to hepato-biliary cancer treatment and research, attempting to balance current evidences with future opportunities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".