Darwin's legacy: the forms, function and sexual diversity of flowers
Bibliographic record
Abstract
Charles Darwin studied floral biology for over 40 years and wrote three major books on plant reproduction. These works have provided the conceptual foundation for understanding floral adaptations that promote cross-fertilization and the mechanisms responsible for evolutionary transitions in reproductive systems. Many of Darwin's insights, gained from careful observations and experiments on diverse angiosperm species, remain remarkably durable today and have stimulated much current research on floral function and the evolution of mating systems. Here I review Darwin's seminal contributions to reproductive biology and provide an overview of the current status of research on several of the main topics to which he devoted considerable effort, including the consequences to fitness of cross- versus self-fertilization, the evolution and function of stylar polymorphisms, the adaptive significance of heteranthery, the origins of dioecy and related gender polymorphisms, and the transition from animal pollination to wind pollination. Post-Darwinian perspectives on floral function now recognize the importance of pollen dispersal and male outcrossed siring success in shaping floral adaptation. This has helped to link work on pollination biology and mating systems, two subfields of reproductive biology that remained largely isolated during much of the twentieth century despite Darwin's efforts towards integration.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".