The estimated number of patients with hepatocellular carcinoma selected for liver transplantation using expanded selection criteria
Bibliographic record
Abstract
Recently, several groups have introduced expanded criteria for selection of patients with hepatocellular carcinoma (HCC) prior to transplant, but the exact number of potential newly recruited patients remains unclear. This registry-based study assessed 270 patients diagnosed with HCC. The potential number of transplant candidates was based on age (< or =65 years), absence of metastases and macro-vascular invasion, and on 12 previously published, expanded selection criteria. A wide range of increase in the number of transplant candidates was observed (12-63% when compared with the number of such candidates who would have been selected solely based on the Milan criteria). The most conservative criteria were Seoul (Kwon, 2007; increase of 12%), Valencia (Silva, 2008; 16%), total tumor volume/alpha-fetoprotein (Toso, 2009; 20%) and UCSF (Yao, 2007; 20%). This data will assist Centers and policy agencies in predicting the need for resources linked to an expansion of criteria.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".