Repeated Spontaneous Clearance of Hepatitis C Virus Infection in the Setting of Long-Term Non-Progression of HIV Infection
Bibliographic record
Abstract
Hepatitis C Virus (HCV) and human immunodeficiency virus (HIV) are global pandemics that affect 170 million and 35 million individuals, respectively. Up to 45% of individuals infected with HCV clear their infections spontaneously - correlating to factors like aboriginal descent and some host specific immune factors. HIV, however, establishes true latency in infected cells and cannot be cured. In the setting of longterm non-progressors (LTNPs) of HIV, a state of immune preservation and low circulating viral load is established. Regarding HIV/HCV co-infection, little is known about the relationship between spontaneous clearance of HCV infection and long-term control of HIV infection without medical intervention. We describe a case of a HIV-infected female defined as a LTNP in whom spontaneous clearance of HCV was documented on multiple occasions. Similar cases should be documented and identified in an effort to develop novel hypotheses about the natural control of these infections and inform research on immune-based interventions to control them.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".