Improved Phylogenomic Taxon Sampling Noticeably Affects Nonbilaterian Relationships
Bibliographic record
Abstract
Despite expanding data sets and advances in phylogenomic methods, deep-level metazoan relationships remain highly controversial. Recent phylogenomic analyses depart from classical concepts in recovering ctenophores as the earliest branching metazoan taxon and propose a sister-group relationship between sponges and cnidarians (e.g., Dunn CW, Hejnol A, Matus DQ, et al. (18 co-authors). 2008. Broad phylogenomic sampling improves resolution of the animal tree of life. Nature 452:745-749). Here, we argue that these results are artifacts stemming from insufficient taxon sampling and long-branch attraction (LBA). By increasing taxon sampling from previously unsampled nonbilaterians and using an identical gene set to that reported by Dunn et al., we recover monophyletic Porifera as the sister group to all other Metazoa. This suggests that the basal position of the fast-evolving Ctenophora proposed by Dunn et al. was due to LBA and that broad taxon sampling is of fundamental importance to metazoan phylogenomic analyses. Additionally, saturation in the Dunn et al. character set is comparatively high, possibly contributing to the poor support for some nonbilaterian nodes.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".