Bibliographic record
Abstract
Background: First isolated in December 2019, SARS-CoV-2 is the agent responsible for the ongoing breakout of COVID-19. Method: We curated an assembly of the first 48 full-length SARS-CoV-2 genomes isolated and sequenced across the world and performed a phylogenetic network analysis to monitor the emergence of genomic divergence in the global SARS-CoV-2 population. Results: We identified regions of the genome that have accumulated mutations producing non-synonymous changes at the protein level, suggesting ongoing adaptation of SARS-CoV-2 to its novel human host. We identified a strong L84S mutational signal in ORF8 (present in 29.16% of genomes) together with 12 variable sites in the region encoding non-structural protein Nsp3 that represent the strongest putative regions under selection in our dataset. We did not detect mutations in the coronavirus spike protein, which is reassuring for the vaccines currently available or are ongoing large-scale clinical trials. Conclusion: Our analysis provides a snapshot in time of a rapidly evolving pandemic based on available data. Our results are in line with previous findings that point to a common ancestor isolated in Wuhan that is likely to have circulated and spread worldwide. © 2021, University of Toronto. All rights reserved.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".