Sexual dimorphism in floral traits of gynodioecious <i>Lobelia siphilitica</i> (Lobeliaceae) is consistent across populations
Bibliographic record
Abstract
In angiosperms, the evolution of gender dimorphism is often correlated with the evolution of sexual dimorphism in floral traits. The magnitude of sexual dimorphism will reflect both sex-specific selection and constraints on evolution in response to this selection. If the evolution of sexual dimorphism is constrained by genetic correlations, then trait means are predicted to evolve more quickly than the magnitude of sexual dimorphism in the same traits. To test whether mean floral traits evolve more quickly than sexual dimorphism in these traits, I measured flower size and flower number of gynodioecious Lobelia siphilitica L. from 10–14 populations across the species’ range. Females produced more flowers than hermaphrodites, but neither mean flower number nor the magnitude of dimorphism in flower number varied among populations. Pistillate flowers were smaller than perfect flowers, and mean flower size varied among populations. However, the magnitude of dimorphism in flower size did not vary. My results suggest that the evolution of sexual dimorphism in flower size, but not necessarily flower number, could be constrained by within- or between-sex genetic correlations in L. siphilitica.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".