Macroevolutionary Patterns of Flowering Plant Speciation and Extinction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Species diversity is remarkably unevenly distributed among flowering plant lineages. Despite a growing toolbox of research methods, the reasons underlying this patchy pattern have continued to perplex plant biologists for the past two decades. In this review, we examine the present understanding of transitions in flowering plant evolution that have been proposed to influence speciation and extinction. In particular, ploidy changes, transitions between tropical and nontropical biomes, and shifts in floral form have received attention and have offered some surprises in terms of which factors influence speciation and extinction rates. Mating systems and dispersal characteristics once predominated as determining factors, yet recent evidence suggests that these changes are not as influential as previously thought or are important only when paired with range shifts. Although range extent is an important correlate of speciation, it also influences extinction and brings an applied focus to diversification research. Recent studies that find that past diversification can predict present-day extinction risk open an exciting avenue for future research to help guide conservation prioritization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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