Canadian Association for the Study of the Liver Single Topic Conference on Hepatitis B Virus: ‘Progress toward hepatitis B elimination in Canada’
Bibliographic record
Abstract
Hepatitis B virus (HBV) infection affects >290 million people worldwide, including ∼250,000 Canadians, and it stands as a leading cause of end-stage liver disease and liver cancer. The World Health Assembly has set goals for HBV elimination by 2030, aiming for a >90% reduction in incidence and a 65% reduction in deaths compared to 2015. However, as of 2023, no countries were on track to achieve these targets. In Canada, challenges in HBV elimination persist due to the lack of a universal birth dose vaccine and interprovincial disparities in screening and care linkage. The Canadian Association for the Study of the Liver (CASL) and the Canadian Hepatitis B Network hosted the Inaugural Progress toward Hepatitis B Elimination Meeting in Calgary, Alberta, Canada (September 29, 2023 to October 1, 2023). This collaborative platform brought together national and international clinicians, laboratory providers, public health researchers, policymakers, and community-based organizations interested in HBV and hepatitis Delta virus (HDV) / HBV coinfection. The workshop was held during the National Day of Truth and Reconciliation (September 30, 2023) to commemorate the tragic legacy of residential schools in Canada, and it highlighted the need to promote meaningful reconciliation with Indigenous peoples. Key outcomes of the summit included establishing objectives for HBV elimination, advocating for adherence to global targets, universal screening and birth dose vaccination, equitable access to antiviral treatment across all provinces/territories, and addressing special populations. This overview highlights the presentations and emphasizes the importance of collaboration among stakeholders, public health agencies, and government entities to strive for HBV elimination in Canada.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.140 | 0.024 |
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".