Hepatitis C Virus in American Indian/Alaskan Native and Aboriginal Peoples of North America
Bibliographic record
Abstract
Liver diseases, such as hepatitis C virus (HCV) infection, are "broken spirit" diseases. The prevalence of HCV infection for American Indian/Alaskan Native (AI/AN) in the United States and Canadian Aboriginals varies; nonetheless, incidence rates of newly diagnosed HCV infection are typically higher relative to non-indigenous people. For AI/AN and Aboriginal peoples risk factors for the diagnosis of HCV infection can reflect that of the general population: predominately male, a history of injection drug use, in midlife years, with a connection with urban centers. However, the face of the indigenous HCV infected individual is becoming increasingly female and younger compared to non-indigenous counterparts. Epidemiology studies indicate that more effective clearance of acute HCV infection can occur for select Aboriginal populations, a phenomenon which may be linked to unique immune characteristics. For individuals progressing to chronic HCV infection treatment outcomes are comparable to other racial cohorts. Disease progression, however, is propelled by elevated rates of co-morbidities including type 2 diabetes and alcohol use, along with human immunodeficiency virus (HIV) co-infection relative to non-indigenous patients. Historical and personal trauma has a major role in the participation of high risk behaviors and associated diseases. Although emerging treatments provide hope, combating HCV-related morbidity and mortality will require interventions that address the etiology of broken spirit diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".