Multiple evolutionary transitions of reproductive strategies in a phylum of aquatic colonial invertebrates
Bibliographic record
Abstract
PHYLOGENIES All_genes_alignment.nex The concatenated mixed alignment consisting of, 13 mitochondrial protein-coding genes as amino acids, mitochondrial ribosomal RNA genes 12S+16S, and nuclear 18S+28S rRNA genes. Gene boundaries and excludes sites are indicated. Fig_2.nex Topology of the Bayesian phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. The analysis was performed in MrBayes5D v. 3.2.6 under the GTR+G model of nucleotide evolution (nucleotides) and the MTZOA+G model (amino acids). The analysis was run for 2.4 million generations; 1.5 million generations were discarded as burn-in. Fig_S3 Topology of the Bayesian phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes (PCGs) as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. The analysis was performed in p4 under the GTR+G model of nucleotide evolution (nucleotides) and the MTZOA+G+F model (amino acids). The +F model component accommodates empirical composition in the amino acid model. The analysis used three separate runs for 300,000 generations; 200,000 generations were discarded as burn-in. Fig_S4 Topology of the maximum likelihood phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. The analysis was performed in RAxML HPC-PTHREADS-SSE3 v. 8.2.12 under the GTR+G (nucleotides) and the MTZOA+G+F models (amino acids). Fig_S5 Topology of the Bayesian phylogenetic analysis of the 12S+16S rRNA gene partition constructed using MrBayes v. 3.2.6 under the GTR + G model. The analysis was run for 20 million generations; 10 million generations were discarded as burn-in. Fig_S6 Topology of the maximum likelihood phylogenetic analysis of the 12S+16S rRNA gene partition constructed using RAxML HPC-PTHREADS-SSE3 v. 8.2.12 under the GTRCAT model. Fig_S7 Topology of the Bayesian phylogenetic analysis of the 18S+28S rRNA gene partition constructed using MrBayes v. 3.2.6 under the GTR + G model. The analysis was run for 20 million generations; 10 million generations were discarded as burn-in. Fig_S8 Topology of the maximum likelihood phylogenetic analysis of the 18S+28S rRNA gene partition constructed using RAxML HPC-PTHREADS-SSE3 v. 8.2.12 under the GTRCAT model. Fig_S9 Topology of the Bayesian phylogenetic analysis of 13 mitochondrial protein-coding genes as amino acids constructed using MrBayes5D v. 3.2.6 under the MTZOA+G model. The analysis was run for 3.7 million generations; 2.5 million generations were discarded as burn-in. Fig_S10 Topology of the maximum likelihood phylogenetic analysis of 13 mitochondrial protein-coding genes as amino acids constructed using RAxML HPC-PTHREADS-SSE3 v. 8.2.12 under the PROTGAMMAMTZOA model. Fig_S11 Topology of the Bayesian phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes (PCGs) as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. The analysis was performed in p4 under the NDCH-C2 model. The analysis used four separate runs for 300,000 generations; 200,000 generations were discarded as burn-in. The NDCH model accommodates compositional tree-heterogeneity and was used because there was a large amount of compositional heterogeneity over the sequences, especially in the PCGs and 12S+16S rRNA data partitions. This is an NDCH model with two composition vectors on each of the three data partitions. Fig_S12 Topology of the Bayesian phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. This analysis excluded all terminals for which less than half of mitogenome genes were available, or which only had one of the two nuclear rRNA genes. The analysis was performed in MrBayes5D v. 3.2.6 under the GTR+G model of nucleotide evolution (nucleotides) and the MTZOA+G model (amino acids). The analysis was run for 350,000 generations; 125,000 generations were discarded as burn-in. Fig_S13 Topology of the maximum likelihood phylogenetic analysis of the mixed concatenated alignment consisting of three partitions: (i) 13 mitochondrial protein-coding genes as amino acids, (ii) mitochondrial ribosomal RNA genes 12S+16S, (iii) nuclear 18S+28S rRNA genes. This analysis excluded all terminals for which less than half of mitogenome genes were available, or which only had one of the two nuclear rRNA genes. The analysis was performed in RAxML HPC-PTHREADS-SSE3 v. 8.2.12 under the GTR+G (nucleotides) and the MTZOA+G+F models (amino acids). ANCESTRAL CHARACTER ESTIMATION: ACE.R R script of the ancestral character estimation carried out in phytools. Reproductive_strategy_numbers.csv Data input file for ACE analysis (reproductive strategies coded as numbers) Reproductive_strategies.xlsx List of reproductive strategies per taxon with the corresponding numerical codes used in the file 'Reproductive_stategies_numbers.csv'. Tree.tre Input tree for ACE analysis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".