From non-A, non-B hepatitis to hepatitis C virus cure
Bibliographic record
Abstract
The hepatitis C virus (HCV) was discovered in the late 1980s. Interferon (IFN)-α was proposed as an antiviral treatment for chronic hepatitis C at about the same time. Successive improvements in IFN-α-based therapy (dose finding, pegylation, addition of ribavirin) increased the rates of sustained virologic response, i.e. the rates of curing HCV infection. These rates were further improved by adding the first available direct-acting antiviral (DAA) drugs to the combination of pegylated IFN-α and ribavirin. An IFN-free era finally started in 2014, yielding rates of sustained virologic response over 90% in patients treated for 8 to 24 weeks with all-oral regimens. Major challenges however remain in implementation of these new treatment strategies, not only in low- to middle-income countries, but also in high-income countries where the price of these therapies is still prohibitive. Elimination of HCV infection through treatment in certain areas is possible but raises major public health issues.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".