Yersinia pestis: New Evidence for an Old Infection
Bibliographic record
Abstract
The successful reconstruction of an ancient bacterial genome from archaeological material presents an important methodological advancement for infectious disease research. The reliability of evolutionary histories inferred by the incorporation of ancient data, however, are highly contingent upon the level of genetic diversity represented in modern genomic sequences that are publicly accessible, and the paucity of available complete genomes restricts the level of phylogenetic resolution that can be obtained. Here we add to our original analysis of the Yersinia pestis strain implicated in the Black Death by consolidating our dataset for 18 modern genomes with single nucleotide polymorphism (SNP) data for an additional 289 strains at over 600 positions. The inclusion of this additional data reveals a cluster of Y. pestis strains that diverge at a time significantly in advance of the Black Death, with divergence dates roughly coincident with the Plague of Justinian (6(th) to 8(th) century AD). In addition, the analysis reveals further clues regarding potential radiation events that occurred immediately preceding the Black Death, and the legacy it may have left in modern Y. pestis populations. This work reiterates the need for more publicly available complete genomes, both modern and ancient, to achieve an accurate understanding of the history of this bacterium.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".