Bibliographic record
Abstract
Chronic hepatitis B infection presents a number of challenges to clinicians. There are additional considerations when defining management strategies for individuals with advanced liver disease, or coinfection, or those at high risk of developing hepatocellular carcinoma (HCC). Treatment of decompensated cirrhosis is particularly important. Evidence suggests that suppression of viral replication through nucleos(t)ide analog therapy leads to longer time to transplantation, improved liver function, and improved survival times. The use of interferon in patients with decompensated hepatitis B is associated with serious complications and is currently contraindicated for these patients by the AASLD Practice Guidelines. Hepatitis B coinfection is often associated with more extensive disease. In patients with HBV/HCV coinfection, one disease is usually dominant and consequently should be the focus of therapy. HIV/HBV coinfection increases the risk of progressive liver disease. Therapeutic agents active against both viruses should be utilized at the correct dose to limit the development of resistance. Agents specific for HBV, e.g., entecavir, enable hepatitis to be treated while avoiding the risk of HIV resistance developing. Dual infection with HBV and HDV is particularly challenging. Nucleos(t)ide analogs are ineffective in treating HDV infection, and there is limited data concerning the efficacy of interferon in this setting. The association between chronic hepatitis B infection and hepatocellular carcinoma (HCC) is well established. In patients at high risk of HCC, screening regimes may be effective. Furthermore, there is an increasing body of evidence indicating that effective suppression of viral replication may be associated with a reduced risk of HCC.
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".