Computational Identification of Reassortments in Avian Influenza Viruses
Bibliographic record
Abstract
The avian influenza virus (AIV) has eight genomic segments (hemagglutinin [HA], neuraminidase [NA], RNA polymerase subunit A [PA], RNA polymerase subunit B1 [PB1], RNA polymerase subunit B2 [PB2], nucleoprotein [NP], nonstructural gene [NS], and matrix protein [M]). The genetic reassortments, recombinations, and mutations lead to a rapid emergence of novel genotypes of the AIVs during their evolution. These emerging viruses provide a large reservoir for pandemic strains. Here we describe a novel computational strategy for genetic reassortment identification. In contrast to the traditional phylogenetic approaches, our method views the genotypes through the modules in networks. Genetic segments with short phylogenetic distance are grouped into modules. Our method is not limited to the number of sequences. We applied this method in reassortment identification of NP segments in H5N1 AIVs. We identified two new potential reassortments for H5N1 AIVs beyond the reported genotypes in literature.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".