Genetic Diversity of Hepatitis B Virus as an Important Factor Associated with Differences in Clinical Outcomes
Bibliographic record
Abstract
Approximately 350 million people worldwide are persistently infected with hepatitis B virus (HBV) [1], which has been classified into 8 genotypes (A–H) by means of molecular evolutionary analyses [2–4]. HBV genotypes have different geographic distributions [5]. Genotype D is ubiquitous and scattered worldwide, whereas genotype A is prevalent in sub-Saharan Africa, North America, and Europe and genotypes B and C are common in Asia. Genotype E is mainly restricted to western Africa, and genotype F is considered to be indigenous to aboriginal populations in Central and South America [6]. In addition, a number of genotype F–specific phylogenetic clusters have been attributed to local populations in different geographic areas [7, 8], such as Argentina [9], Venezuela [10], and Central America [11], as well as in the drainage area of the Yukon and Kuskokwim Rivers in southwestern Alaska [12]. Genotype F also has been detected sporadically in Brazil [13], North America [6, 14], Europe [8], and Polynesia [15]. Genotype H has been found in Mexico and Central America [4, 6]. Genotype G has been detected infrequently, and its epidemiologic profile is unclear
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".