Assessing what is needed to resolve a molecular phylogeny: simulations and empirical data from emydid turtles
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Phylogenies often contain both well-supported and poorly supported nodes. Determining how much additional data might be required to eventually recover most or all nodes with high support is an important pragmatic goal, and simulations have been used to examine this question. Most simulations have been based on few empirical loci, and suggest that well supported phylogenies can be determined with a very modest amount of data. Here we report the results of an empirical phylogenetic analysis of all 10 genera and 25 of 48 species of the new world pond turtles (family Emydidae) based on one mitochondrial (1070 base pairs) and seven nuclear loci (5961 base pairs), and a more biologically realistic simulation analysis incorporating variation among gene trees, aimed at determining how much more data might be necessary to recover weakly-supported nodes with strong support. RESULTS: Our mitochondrial-based phylogeny was well resolved, and congruent with some previous mitochondrial results. For example, all genera, and all species except Pseudemys concinna, P. peninsularis, and Terrapene carolina were monophyletic with strong support from at least one analytical method. The Emydinae was recovered as monophyletic, but the Deirochelyinae was not. Based on nuclear data, all genera were monophyletic with strong support except Trachemys, and all species except Graptemys pseudogeographica, P. concinna, T. carolina, and T. coahuila were monophyletic, generally with strong support. However, the branches subtending most genera were relatively short, and intergeneric relationships within subfamilies were mostly unsupported. Our simulations showed that relatively high bootstrap support values (i.e. >or= 70) for all nodes were reached in all datasets, but an increase in data did not necessarily equate to an increase in support values. However, simulations based on a single empirical locus reached higher overall levels of support with less data than did the simulations that were based on all seven empirical nuclear loci, and symmetric tree distances were much lower for single versus multiple gene simulation analyses. CONCLUSION: Our empirical results provide new insights into the phylogenetics of the Emydidae, but the short branches recovered deep in the tree also indicate the need for additional work on this clade to recover all intergeneric relationships with confidence and to delimit species for some problematic groups. Our simulation results suggest that moderate (in the few-to-tens of kb range) amounts of data are necessary to recover most emydid relationships with high support values. They also suggest that previous simulations that do not incorporate among-gene tree topological variance probably underestimate the amount of data needed to recover well supported phylogenies.
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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 | 0.001 |
| 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 it