Bibliographic record
Abstract
Recent developments in the treatment and prevention of hepatitis B virus (HBV) infections warrant revisiting important epidemiological questions, such as how prevalent is chronic HBV infection in Canada, in which Canadian subpopulations are HBV prevalence rates the highest, in what percentage of infected individuals is the virus actively replicating, and how many infected Canadians are candidates for antiviral therapy? Currently available data suggest the overall prevalence of HBV-infected individuals in the general population is approximately 2%, with 5% to 10% having serological evidence of previous HBV infection. In high risk groups, such as street-connected individuals, Aboriginals and immigrants from endemic areas, these rates of viral prevalence and serological evidence of previous HBV infection are approximately two to 10 and five to 10 times higher, respectively, than in the general population. Candidates for antiviral therapy range from less than 1% of infected Aboriginals to 15% to 30% of Asians with chronic HBV. From these data, it is clear that chronic HBV remains an important public health problem in this country. Hence, resources must be identified to enhance Canadians' awareness of HBV infection, maintain, if not expand, efforts to identify and implement safe and effective antiviral therapy for HBV-infected individuals, and continue programs for universal vaccination to prevent new HBV infections.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".