On Rooting and Dating Viral Trees With a Changing Evolutionary Rate Following Host-Switching
Bibliographic record
Abstract
Viral host-switching from host H1 to host H2 is often associated with changes in viral evolutionary rate r. The pre-switching rate r1 in H1 may stay the same or increase/decrease to a new rate r2 in H2 during the host-switching and host-adapting process, depending on the difference between H1 and H2. The changing rate has previously been modeled by a linear function when the time interval is short but is better modeled by a sigmoidal function. The author presents the mathematical model, illustrates its application, and implements the rooting and dating methods in a new version of the user-friendly TRAD program, which is freely available at https://dambe.bio.uottawa.ca/TRAD/TRAD.aspx. Application of the method to a phylogeny of early SARS-CoV-2 genomes revealed (i) an increase in r in late February 2020 contributed mainly by the D614G lineage, (ii) a significantly better fit of the sigmoidal-rate model to the SARS-CoV-2 evolution than the constant-rate model, and (iii) the common ancestor of the included SARS-CoV-2 genomes dated to November 20, 2019.
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 | 0.000 |
| 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".