The distribution of sexual function in the flowering plant: from monoecy to dioecy
Bibliographic record
Abstract
Abstract In flowering plants, male and female functions are usually closely associated in the same flowers, as predicted by resource allocation theory. However, the benefits of outbreeding can lead to unisexual flowers and the physiological control of their distribution across the plant (monoecy). Monoecy is thought to be a major route to dioecy (separation of sexual function of different individuals). The developmental and functional problems associated with unisexual flowers may thus be solved at the level of the evolution of monoecy. Consequently, the evolution of dioecy from monoecy requires mutations in only a single gene. Here various scenarios (conceptual models) are presented for the evolution of monoecy and dioecy, including scenarios consistent with known cases of single-gene control of dioecy, such as in Populus, and the artificial breeding of dioecy from monoecy experimentally achieved in Zea and Cucumis. Attention is also drawn here to the phenomenon of pleogamy, the minor or occasional occurrence of additional sex morphs within a species, which may provide important information about the genetic and developmental control of various sexual systems. This article is part of the theme issue ‘Sex determination and sex chromosome evolution in land plants’.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| 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".