Analysis of the effects of mating systems on lineage diversification across multiple genera
Bibliographic record
Abstract
Summary The transition from outcrossing to self-fertilization is a major evolutionary trend in plants, with selfing long hypothesized an evolutionary dead end. Recent theories suggest that elevated extinction rates may be restricted to highly selfing rather than mixed-mating populations. Previous analyses of the effects of mating systems on diversification found mixed results, varying by focal clades and potentially suffering from several limitations. We collected data on three mating-system-related characters. We also collected life form data to indirectly distinguish between mixed mating and highly selfing. We estimated speciation and extinction rates for character states, and state transition rates in 27 genera. We find that outcrossing lineages diversify at higher rates than selfing lineages, while the impact of mating systems on speciation is not consistent across genera. Among self-compatible lineages, annuals/short-lived exhibit significantly lower diversification rates than perennials. Models incorporating hidden states often provide a better fit than those without. The results suggest that selfing lineages overall have lower diversification rates. This may be primarily contributed by elevated extinction rates in highly selfing lineages, which may also explain the prevalence of mixed-mating systems. However, the influences of mating systems on diversification may be often driven by other factors correlated with mating system transitions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".