An In-depth Analysis of a Multilocus Phylogeny Identifies <i>Leu</i> S As a Reliable Phylogenetic Marker for the Genus <i>Pantoea</i>
Bibliographic record
Abstract
Partial sequences of six core genes (fusA, gyrB, leuS, pyrG, rlpB, and rpoB) of 37 strains of Pantoea species were analyzed in order to obtain a comprehensive view regarding the phylogenetic relationships within the Pantoea genus and compare tree topologies to identify gene(s) for reliable species and subspecies differentiation. All genes used in this study were effective at species-level delineation, but the internal nodes represented conflicting common ancestors in fusA- and pyrG-based phylogenies. Concatenated gene phylogeny gave the expected DNA relatedness, underscoring the significance of a multilocus sequence analysis. Pairwise comparison of topological distances and percent similarities indicated a significant differential influence of individual genes on the concatenated tree topology. leuS- and fusA-inferred phylogenies exhibited, respectively, the lowest (4) and highest (52) topological distances to the concatenated tree. These correlated well with high (96.3%) and low (64.4%) percent similarities of leuS- and fusA-inferred tree topologies to the concatenated tree, respectively. We conclude that the concatenated tree topology is strongly influenced by the gene with the highest number of polymorphic and non-synonymous sites in the absence of significant recombination events.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".