Bibliographic record
Abstract
Spontaneous loss of hepatitis B e antigen (HBeAg) followed by seroconversion to anti-HBe usually coincides with normalization of serum alanine aminotransferase (ALT) levels, reduction in HBV DNA in serum (< 1 x 10(6) copies/mL), and a marked reduction in hepatic inflammation. Licensed antiviral therapies are the interferon (IFN) alphas and the nucleoside analogue lamivudine. Both drugs enhance the rate at which HBeAg seroconversion takes place and thus reduce progression of disease. These therapeutic agents are ineffective if given when there is no ongoing hepatitis (i.e., normal ALT), and their efficacy is greatest in individuals with the most active disease. The effectiveness of these two classes of drugs is similar, and it is possible that the two therapies combined are more effective than monotherapy with either drug. A high side-effect profile and the high risk of further morbidity when given to patients with decompensated disease limit the use of IFN-alpha. When prescribing lamivudine, drug resistance that increases with duration of therapy and the potential risk of a severe flare of hepatitis with sudden cessation of therapy, probably greatest in patients with cirrhosis, are realistic concerns. Both patient and physician need to recognize the need for close monitoring both during and after cessation of any antiviral therapy for hepatitis B.
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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".