Does a patient qualify for liver transplantation after the down-staging of hepatocellular carcinoma?
Bibliographic record
Abstract
We searched the MEDLINE database (PubMed) and the Cochrane Library to identify studies evaluating down-staging and locoregional therapy for hepatocellular carcinoma (HCC) before liver transplantation (LT).The search was restricted to studies written in English and published from 1995 to 2010.The key words for the search included down-staging, liver transplantation, hepatocellular carcinoma, locoregional therapy, staging, treatment outcomes, radio frequency ablation, and transarterial chemoembolization.All published articles and abstracts were reviewed and screened by 2 members of the working group independently (F.Y.Y. and S.B.), and relevant articles and abstracts were selected for further review by the group.The group agreed on 5 key questions for addressing this topic, and each of the 5 members of the working group led the review and summary of an assigned question.The summary was reviewed and approved by all members of the working group.The level of evidence was graded according to the standards of the Oxford Centre for Evidence-Based Medicine and was approved by all group members.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".