Evolutionary Relationships of Unclassified Coronaviruses in Canadian Bat Species
Bibliographic record
Abstract
Bats are recognized as natural reservoirs for an array of diverse viruses, particularly coronaviruses, which have been linked to major human diseases like SARS-CoV and MERS-CoV. These viruses are believed to have originated in bats, highlighting their role in virus ecology and evolution. Our study focuses on the molecular characterization of bat-derived coronaviruses (CoVs) in Canada. Tissue samples from 500 bat specimens collected in Canada were analyzed using pan-coronavirus RT-PCR assays to detect the presence of CoVs from four genera: Alpha-CoVs, Beta-CoV, Gamma-CoV, and Delta-CoV. Phylogenetic analysis was performed targeting the RNA-dependent RNA polymerase (RdRP) gene. Our results showed an overall 1.4% CoV positivity rate in our bat sample size. Phylogenetic analysis based on the ~600 bp sequences led to the identification of an unclassified subgenus of Alpha-CoV, provisionally named Eptacovirus. The findings contribute to a better understanding of the diversity and evolution of CoVs found in the bat species of Canada. The current study underscores the significance of bats in the epidemiology of CoVs and enhances the knowledge of their genetic diversity and potential impact on global public health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".