Bibliographic record
Abstract
Hepatitis B has been a major challenge within the field of transplantation over the past few decades. Due to aggressive recurrence post-transplant, patients with hepatitis B have been excluded from the benefits of both solid organ and bone marrow transplants. Progress has been made, however, through an improved understanding of the biology of hepatitis B and the development of new antiviral strategies that can reliably suppress the virus. Patients with hepatitis B are now candidates for transplantation in an increasing number of circumstances. Careful pre-transplant evaluation is mandatory, together with a tailored antiviral regimen depending on the replicative status of the virus and the organ being transplanted. Minimizing steroid dose following transplantation is an important part of the strategy to reduce the risk of viral reactivation. Lamivudine has been an important development and it has assumed an increasing role in the management of these patients. As additional antivirals are developed, increasingly effective drug combinations will prevent viral recurrence as well as the emergence of drug-resistant mutants, which plagues the use of single agents. It is a rapidly evolving field and there is every reason for continued optimism.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".