Exploration of Plastid Phylogenomic Conflict Yields New Insights into the Deep Relationships of Leguminosae
Bibliographic record
Abstract
Phylogenomic analyses have helped resolve many recalcitrant relationships in the angiosperm tree of life, yet phylogenetic resolution of the backbone of the Leguminosae, one of the largest and most economically and ecologically important families, remains poor due to generally limited molecular data and incomplete taxon sampling of previous studies. Here, we resolve many of the Leguminosae's thorniest nodes through comprehensive analysis of plastome-scale data using multiple modified coding and noncoding data sets of 187 species representing almost all major clades of the family. Additionally, we thoroughly characterize conflicting phylogenomic signal across the plastome in light of the family's complex history of plastome evolution. Most analyses produced largely congruent topologies with strong statistical support and provided strong support for resolution of some long-controversial deep relationships among the early diverging lineages of the subfamilies Caesalpinioideae and Papilionoideae. The robust phylogenetic backbone reconstructed in this study establishes a framework for future studies on legume classification, evolution, and diversification. However, conflicting phylogenetic signal was detected and quantified at several key nodes that prevent the confident resolution of these nodes using plastome data alone. [Leguminosae; maximum likelihood; phylogenetic conflict; plastome; recalcitrant relationships; stochasticity; systematic error.].
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".