The 3rd Canadian Symposium on Hepatitis C Virus: Expanding Care in the Interferon-Free Era
Bibliographic record
Abstract
Hepatitis C virus (HCV) currently infects approximately 250,000 individuals in Canada and causes more years of life lost than any other infectious disease in the country. In August 2011, new therapies were approved by Health Canada that have achieved higher response rates among those treated, but are poorly tolerated. By 2014⁄2015, short-course, well-tolerated treatments with cure rates >95% will be available. However, treatment uptake is poor due to structural, financial, geographical, cultural and social barriers. As such, 'Barriers to access to HCV care in Canada' is a crucial topic that must be addressed to decrease HCV disease burden and potentially eliminate HCV in Canada. Understanding how to better care for HCV-infected individuals requires integration across multiple disciplines including researchers, clinical services and policy makers to address the major populations affected by HCV including people who inject drugs, baby boomers, immigrants and Aboriginal and⁄or First Nations people. In 2012, the National CIHR Research Training Program in Hepatitis C organized the 1st Canadian Symposium on Hepatitis C Virus (CSHCV) in Montreal, Quebec. The 2nd CSHCV was held in 2013 in Victoria, British Columbia. Both symposia were highly successful, attracting leading international faculty with excellent attendance leading to dialogue and knowledge translation among attendees of diverse backgrounds. The current article summarizes the 3rd CSHCV, held February 2014, in Toronto, Ontario.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.032 | 0.005 |
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".