Bibliographic record
Abstract
Hepatitis C virus (HCV) infection is a common cause of liver disease in the UK. HCV can cause liver failure and liver cancer, and is a frequent indication for liver transplantation. HCV infection can be cured by antiviral therapy. Standard therapy includes the combination of pegylated interferon and ribavirin (PEG-IFN/RIBA) for 24 or 48 weeks, according to HCV genotype.1–3 A sustained virological response (SVR), defined as undetectable serum HCV RNA six months after cessation of therapy, indicates successful treatment, almost certainly cure. Published registration trials reported encouraging SVR rates of 42–52% for genotype 1 and 77–88% for genotypes 2/3.1–3 However, analysis of the combined experience of six European and US centres reported significantly worse results.4 In that report, the response rate to treatment of genotype 1 infection with pegylated IFN alpha 2a and ribavirin was only 36%. Also, a large US based prospective randomised study reported response rates of 29–34%, depending on the dose of ribavirin used.5 In contrast, a Canadian study that prospectively tracked patients receiving HCV treatment reported SVR rates …
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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".