NASPGHAN Practice Guidelines
Bibliographic record
Abstract
Hepatitis C virus (HCV) is an RNA virus that affects >180 million individuals worldwide with a high propensity for chronic infection. Children with HCV infection differ from adults in several ways including some modes of transmission, rates of clearance, progression of fibrosis, and the duration of potential chronic infection when acquired at birth. Since the discovery of HCV in 1989, there have been significant advances in the understanding of the virology and natural history of chronic HCV infection in children. In addition, there are now several treatment options for children with chronic hepatitis C infection and many new therapies on the horizon. As a consequence, the North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition brought together experts in pediatric hepatology to review the available data in children and provide clinicians with approaches to the diagnosis, management, and prevention of HCV infection in children and adolescents. The guideline details the epidemiology and natural history of HCV infection in children, the diagnostic workup, monitoring and treatment of disease, and provides an update on future treatment options and areas of research.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.107 | 0.067 |
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".