Patterns of clade support across the major lineages of moss phylogeny
Bibliographic record
Abstract
Relationships among the major branches of moss phylogeny are understudied compared with other major land-plant groups. We addressed this by surveying 14-17 plastid genes from taxa representing the major lineages, using different phylogenetic methods (parsimony, likelihood) and codon- and gene-based data partitioning schemes (likelihood). Our phylogenetic inferences generally corroborated the best supported clades across multiple recent studies, with comparable or higher levels of clade support here. We resolved persistent ambiguities with strong to moderate support across analyses, including several early nodes in subclass Dicranidae, and relationships among other subclasses of peristomate mosses. In particular, we resolved a sister-group relationship between Bryidae and Dicranidae, between these subclasses and Timiidae, and between this entire clade and Funariidae. We consistently recovered Tetraphidopsida (a nematodontous class) as the sister group of arthrodontous mosses (Bryopsida), although with only weak support. Strongly conflicting arrangements at the base of moss phylogeny concerning Takakiopsida and Sphagnopsida, two non-peristomate moss lineages, were inferred in parsimony and likelihood analysis, but this depended on how base-frequency parameters were estimated and how data were partitioned in likelihood analysis. Relationships inferred for the remaining peristomate and non-peristomate moss clades, and their associated support values, were otherwise broadly congruent across analyses.
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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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".