Addressing hepatitis C in the foreign-born population: A key to hepatitis C virus elimination in Canada
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) is the leading cause of death from infectious disease in Canada. Immigrants are an important group who are at increased risk for HCV; they account for a disproportionate number of all HCV cases in Canada (~30%) and have approximately a twofold higher prevalence of HCV (~2%) than those born in Canada. HCV-infected immigrants are more likely to develop cirrhosis and hepatocellular carcinoma and are more likely to have a liver-related death during a hospitalization than HCV-infected non-immigrants. Several factors, including lack of routine HCV screening programs in Canada for immigrants before or after arrival, lack of awareness on the part of health practitioners that immigrants are at increased risk of HCV and could benefit from screening, and several patient- and health system-level barriers that affect access to health care and treatment likely contribute to delayed diagnosis and treatment uptake. HCV screening and engagement in care among immigrants can be improved through reminders in electronic medical records that prompt practitioners to screen for HCV during clinical visits and implementation of decentralized community-based screening strategies that address cultural and language barriers. In conclusion, early screening and linkage to care for immigrants from countries with an intermediate or high prevalence of HCV would not only improve the health of this population but will be key to achieving HCV elimination in Canada. This article describes the unique barriers encountered by the foreign-born population in accessing HCV care and approaches to overcoming these barriers.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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