Web Visualization for Spatiotemporal Genomic Epidemiology, Annotation, and Mutation Dynamics of Orthohantavirus hantanense Using Nextstrain
Bibliographic record
Abstract
The phylogeographic inference approach aims to connect genomic data with epidemiology to understand the spread and evolution of pathogens using visualization of spatiotemporal reconstructions. Orthohantavirus hantanense (HTNV), the causative agent of hemorrhagic fever with renal syndrome (HFRS), represents a significant global public health concern. Here, we introduce a localized Nextstrain platform for HTNV, offering a comprehensive resource for facilitating spatiotemporal genomic surveillance and the study of evolutionary dynamics of viral genomes. Nextstrain enables web-based visualization and simple sharing of graphic and numeric data through unique web addresses. The Nextstrain build for HTNV stands out for its user-friendly interface and is readily accessible online at https://nextstrain.org/community/KU-MV/Hantavirus. This study provides valuable insights into genomic surveillance, viral phylodynamics, and the evolutionary history of orthohantaviruses for the development of public health policies against endemic HFRS outbreaks.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".