Key innovations within a geographical context in flowering plants: towards resolving Darwin’s abominable mystery
Bibliographic record
Abstract
Elucidating factors associated with diversification have been attempted in lineages as diverse as birds, mammals and angiosperms, yet has met with limited success. In flowering plants, the ambiguity of associations between traits and diversification has sparked debate since Darwin's description of angiosperm diversification as an 'abominable mystery'. Recent work has found that diversification is often diversity-dependent, suggesting that species richness depends on geographical area available more than on traits or the time available to accumulate species. Here, we undertake phylogenetic generalized least squares analyses that jointly examine the effects of age, ecoregion area and four ecological traits on diversification in 409 angiosperm families. Area explained the most variation, dwarfing the effect of traits and age, suggesting that diversity-dependent diversification is controlled by ecological limits. Within the context of area, however, traits associated with biotic pollination (zygomorphy) exhibited the greatest effect, possibly through the evolution of specialization.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".