Interplay between co-divergence and cross-species transmission in the evolutionary history of bat coronaviruses
Bibliographic record
Abstract
Coronaviruses (CoVs) have been documented in almost every species of bat sampled. Bat CoVs exhibit both extensive genetic diversity and a broad geographic range, indicative of a long-standing host association. Despite this, the respective roles of long-term virus-host co-divergence and cross-species transmission (host-jumping) in the evolution of bat coronaviruses are unclear. Using a phylogenetic approach we provide evidence that CoV diversity in bats is shaped by both species richness and their geographical distribution, and that CoVs exhibit clustering at the level of bat genera, with these genus-specific clusters largely associated with distinct CoV species. Co-phylogenetic analyses revealed that cross-species transmission has been more common than co-divergence across coronavirus evolution as a whole, and that cross-species transmission events were more likely between sympatric bat hosts. Notably, however, an analysis of the CoV RNA polymerase phylogeny suggested that many such host-jumps likely resulted in short-term spill-over infections, with little evidence for sustained onward transmission in new co-roosting host species.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".