Hepatitis B e Antigen-Positive Chronic Hepatitis B: Natural History and Treatment
Bibliographic record
Abstract
The natural history of hepatitis B e antigen (HBeAg)-positive chronic hepatitis B is very heterogeneous. Age at acquisition is a major factor in determining the natural history of chronic infection. The vigor of the host immune response to the virus, viral factors (genotype, core promoter mutations, and duration of viral replication) as well as exogenous factors (alcohol, immune suppression) all influence the severity of disease. The goal of antiviral therapy is HBeAg seroconversion, and preferably HB surface Ag seroconversion as this latter end-point is associated with sustained immune control and the halting of disease progression. Although peginterferon is now considered as the first line of therapy for HBeAg-positive chronic hepatitis B, in most cases there are circumstances where nucleos(t)ide analogues are indicated (e.g., decompensated liver disease) for those requiring cancer chemotherapy/other immunosuppressive agents and for those with contraindications to interferon. The major challenge for the clinician using these agents is the emergence of antiviral drug resistance. Long-term immune control of viral replication is key to improving patient outcome.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".