Hepatitis C: The beginning of the end—key elements for successful European and national strategies to eliminate HCV in Europe
Bibliographic record
Abstract
Hepatitis C virus (HCV) infection is a major public health problem in the European Union (EU). An estimated 5.6 million Europeans are chronically infected with a wide range of variation in prevalence across European Union countries. Although HCV continues to spread as a largely "silent pandemic," its elimination is made possible through the availability of the new antiviral drugs and the implementation of prevention practices. On 17 February 2016, the Hepatitis B & C Public Policy Association held the first EU HCV Policy Summit in Brussels. This summit was an historic event as it was the first high-level conference focusing on the elimination of HCV at the European Union level. The meeting brought together the main stakeholders in the field of HCV: clinicians, patient advocacy groups, representatives of key institutions and regional bodies from across European Union; it served as a platform for one of the most significant disease elimination campaigns in Europe and culminated in the presentation of the HCV Elimination Manifesto, calling for the elimination of HCV in Europe by 2030. The launch of the Elimination Manifesto provides a starting point for action in order to make HCV and its elimination in Europe an explicit public health priority, to ensure that patients, civil society groups and other relevant stakeholders will be directly involved in developing and implementing HCV elimination strategies, to pay particular attention to the links between hepatitis C and social marginalization and to introduce a European Hepatitis Awareness Week.
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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 | 0.050 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".