Hepatitis C: The beginning of the end—key elements for successful European and national strategies to eliminate HCV in Europe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it