Animal evolution — A fully-resolved phylogenomic tree argues against the Cambrian explosion hypothesis
Bibliographic record
Abstract
Recently, Rokas et al. (2005) reported that the animal phylogeny could not be resolved despite the use of 50 genes from 17 animal species.Furthermore, the authors concluded that "the lack of resolution" observed in their tree constitutes a positive signature for "an extreme compression of the metazoan radiation."Hence, their work apparently supports the Cambrian explosion hypothesis.However, we suspect that the profound influence of taxon sampling on phylogenetic inference was underestimated, thus leading to erroneous conclusions about the mode and tempo of animal evolution.To substantiate this point of view, we assembled a taxon-rich phylogenomic data set.When including a slowly-evolving nematode we obtained a fully-resolved tree of animals, whereas using a fast-evolving nematode reproduced the artefacts and the lack of resolution observed by Rokas et al.The explanation for this dramatic change lies in the large amount of non-phylogenetic signal introduced by the fastevolving nematode that annihilates the genuine phylogenetic signal.Two conclusions of general interest can be deduced from our analyses: (1) based on current data, the animal tree is fully resolved, which argues against the Cambrian explosion hypothesis; and (2) an adequate sampling (i.e.including slowly-evolving species) is crucial to reduce non-phylogenetic signals in genome-scale phylogenetic inference.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".