Multigene Analyses of Bilaterian Animals Corroborate the Monophyly of Ecdysozoa, Lophotrochozoa, and Protostomia
Bibliographic record
Abstract
Almost a decade ago, a new phylogeny of bilaterian animals was inferred from small-subunit ribosomal RNA (rRNA) that claimed the monophyly of two major groups of protostome animals: Ecdysozoa (e.g., arthropods, nematodes, onychophorans, and tardigrades) and Lophotrochozoa (e.g., annelids, molluscs, platyhelminths, brachiopods, and rotifers). However, it received little additional support. In fact, several multigene analyses strongly argued against this new phylogeny. These latter studies were based on a large amount of sequence data and therefore showed an apparently strong statistical support. Yet, they covered only a few taxa (those for which complete genomes were available), making systematic artifacts of tree reconstruction more probable. Here we expand this sparse taxonomic sampling and analyze a large data set (146 genes, 35,371 positions) from a diverse sample of animals (35 species). Our study demonstrates that the incongruences observed between rRNA and multigene analyses were indeed due to long-branch attraction artifacts, illustrating the enormous impact of systematic biases on phylogenomic studies. A refined analysis of our data set excluding the most biased genes provides strong support in favor of the new animal phylogeny and in addition suggests that urochordates are more closely related to vertebrates than are cephalochordates. These findings have important implications for the interpretation of morphological and genomic data.
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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 | 0.002 | 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 | 0.001 |
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".