Progress towards a hepatitis C virus vaccine
Bibliographic record
Abstract
New drugs to treat hepatitis C are expected to be approved over the next few years which promise to cure nearly all patients. However, due to issues of expected drug resistance, suboptimal activity against diverse hepatitis C virus (HCV) genotypes and especially because of their extremely high cost, it is unlikely that these HCV drugs will substantially reduce the world's HCV carrier population of around 170 million in the near future or the estimated global incidence of millions of new HCV infections. For these reasons, there is an urgent need to develop a prophylactic HCV vaccine and also to determine if therapeutic vaccines can aid in the treatment of chronically infected patients. After much early pessimism on the prospects for an effective prophylactic HCV vaccine, our recent knowledge of immune correlates of protection combined with the demonstrated immunogenicity and protective animal efficacies of various HCV vaccine candidates now allows for realistic optimism. This review summarizes the current rationale and status of clinical and experimental HCV vaccine candidates based on the elicitation of cross-neutralizing antibodies and broad cellular immune responses to this highly diverse virus.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".