On the Age of Eukaryotes: Evaluating Evidence from Fossils and Molecular Clocks
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Bibliographic record
Abstract
Our understanding of the phylogenetic relationships among eukaryotic lineages has improved dramatically over the few past decades thanks to the development of sophisticated phylogenetic methods and models of evolution, in combination with the increasing availability of sequence data for a variety of eukaryotic lineages. Concurrently, efforts have been made to infer the age of major evolutionary events along the tree of eukaryotes using fossil-calibrated molecular clock-based methods. Here, we review the progress and pitfalls in estimating the age of the last eukaryotic common ancestor (LECA) and major lineages. After reviewing previous attempts to date deep eukaryote divergences, we present the results of a Bayesian relaxed-molecular clock analysis of a large dataset (159 proteins, 85 taxa) using 19 fossil calibrations. We show that for major eukaryote groups estimated dates of divergence, as well as their credible intervals, are heavily influenced by the relaxed molecular clock models and methods used, and by the nature and treatment of fossil calibrations. Whereas the estimated age of LECA varied widely, ranging from 1007 (943-1102) Ma to 1898 (1655-2094) Ma, all analyses suggested that the eukaryotic supergroups subsequently diverged rapidly (i.e., within 300 Ma of LECA). The extreme variability of these and previously published analyses preclude definitive conclusions regarding the age of major eukaryote clades at this time. As more reliable fossil data on eukaryotes from the Proterozoic become available and improvements are made in relaxed molecular clock modeling, we may be able to date the age of extant eukaryotes more precisely.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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