Insights into the ancestral flowers of Ranunculales
Bibliographic record
Abstract
Abstract The question of the origin of petals has long been debated in the botanical literature. Ranunculales are characterized by a spectacular floral diversity, particularly at the perianth level. Recent progress in understanding the genetic bases of floral organ identity suggests a single origin for petals in Ranunculaceae, contrasting with the traditional morphological hypothesis of repeated evolution. However, perianth evolution at the ordinal level remains incompletely understood. Recent advances in the elucidation of phylogenetic relationships in the order now provide a new opportunity to study character evolution with model-based methods. We used ancestral state reconstruction methods that take into account various sources of uncertainty to reconstruct the evolution of floral traits at the scale of Ranunculales using a consensus phylogenetic framework of 144 terminal species representing all families in the order. Ancestrally, Ranunculales probably had three trimerous whorls of perianth organs differentiated into two categories of petaloid organs differing in their shape. Each whorl was further lost or duplicated. Moreover, our results support the hypothesis of a single origin of highly specialized (elaborate) nectariferous petals in Ranunculaceae.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".