The Consensus Hepatitis C Cascade of Care: Standardized Reporting to Monitor Progress Toward Elimination
Bibliographic record
Abstract
Cascade-of-care (CoC) monitoring is an important component of the response to the global hepatitis C virus (HCV) epidemic. CoC metrics can be used to communicate, in simple terms, the extent to which national and subnational governments are advancing on key targets, and CoC findings can inform strategic decision-making regarding how to maximize the progression of individuals with HCV to diagnosis, treatment, and cure. The value of reporting would be enhanced if a standardized approach were used for generating CoCs. We have described the Consensus HCV CoC that we developed to address this need and have presented findings from Denmark, Norway, and Sweden, where it was piloted. We encourage the uptake of the Consensus HCV CoC as a global instrument for facilitating clear and consistent reporting via the World Health Organization (WHO) viral hepatitis monitoring platform and for ensuring accurate monitoring of progress toward WHO's 2030 hepatitis C elimination targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".