Visualizing and Assessing Phylogenetic Congruence of Core Gene Sets: A Case Study of the γ-Proteobacteria
Bibliographic record
Abstract
Here, we address a much-debated topic: is there or is there not an organismal tree of gamma-proteobacteria that can be unambiguously inferred from a core of shared genes? We apply several recently developed analytical methods to this problem, for the first time. Our heat map analyses of P values and of bootstrap bipartitions show the presence of conflicting phylogenetic signals among these core genes. Our synthesis reconstruction suggests that at least 10% of these genes have been laterally transferred during the divergence of the gamma-proteobacteria, and that for most of the rest, there is too little phylogenetic signal to permit firm conclusions about the mode of inheritance. Although there is clearly a central tendency in this data set (it is far from random), lateral gene transfers cannot be ruled out. Instead of an organismal tree, we propose that these core genes could be used to define a more subtle and partially reticulated pattern of relationships.
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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".