Morphology supports the setaphyte hypothesis: mosses plus liverworts form a natural group
Bibliographic record
Abstract
The origin and early diversification of land plants is one of the major unresolved problems in evolutionary biology. Occurring nearly half a billion years ago, the transmigration of green organisms to land changed the landscape and provided the food source for terrestrial life to invade a vast uninhabited space, adapt and radiate. Although bryophytes (mosses, liverworts and hornworts) are often regarded as the earliest terrestrial organisms, the order of their divergence remains contentious even as molecular analyses become more conclusive with expanded taxon sampling, massive genetic data and more sophisticated methods of analysis (Cox et al. 2018; Morris et al. 2018). Indeed, virtually every combination of relationships among bryophytes has been proposed based on molecules (Qiu et al. 2006; Wickett et al. 2014; Cox et al. 2018). Fortunately, in 2018 it appears that we are approaching a consensus based on molecules, and that is that although bryophytes may or may not be monophyletic, mosses plus liverworts form a natural group (Puttick et al. 2018). In this essay, we point out that this inference is neither new nor surprising as it has been the fundamental conclusion of morphological analyses for over 25 years starting with an exhaustive cladistic analysis of characters associated with motile cell development in green plants (Garbary et al. 1993).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".