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
Among dioecious flowering plants, females and males often differ in a range of morphological, physiological, and life-history traits. This is referred to as sexual dimorphism, and understanding why it occurs is a central question in evolutionary biology. Our review documents a range of sexually dimorphic traits in angiosperm species, discusses their ecological consequences, and details the genetic and evolutionary processes that drive divergence between female and male phenotypes. We consider why sexual dimorphism in plants is generally less well developed than in many animal groups, and also the importance of sexual and natural selection in contributing to differences between the sexes. Many sexually dimorphic characters, including both vegetative and flowering traits, are associated with differences in the costs of reproduction, which are usually greater in females, particularly in longer-lived species. These differences can influence the frequency and distribution of females and males across resource gradients and within heterogeneous environments, causing niche differences and the spatial segregation of the sexes. The interplay between sex-specific adaptation and the breakdown of between-sex genetic correlations allows for the independent evolution of female and male traits, and this is influenced in some species by the presence of sex chromosomes. We conclude by providing suggestions for future work on sexual dimorphism in plants, including investigations of the ecological and genetic basis of intraspecific variation, and genetic mapping and expression studies aimed at understanding the genetic architecture of sexually dimorphic trait variation.
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.
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) | 0.001 | 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