Correlated effects of selection for flower size in <i>Raphanus raphanistrum</i>
Bibliographic record
Abstract
The evolution of flower size may be constrained by trade-offs between flower size and other plant traits. The aim of this study was to determine how selection on flower size affects both reproductive and vegetative traits. Raphanus raphanistrum L. was used as the study species. Artificial selection for small and large petal size was carried out for two generations. We measured the realized heritability of flower size and recorded flower production, time to flowering, plant size, and seed production in the two selection lines. The realized heritability was h2 = 0.49. Our study, therefore, showed that R. raphanistrum has potential for rapid evolutionary change of floral size. The lines with large flowers produced smaller seeds and started to flower later than the lines with small flowers. There was no trade-off between flower size and flower number, but the lines selected for large flower size had more flowers and a larger plant size than lines selected for small flowers. Estimates of restricted maximum likelihood (REML) analysis of pedigrees also showed that flower size had a positive genetic correlation with start of flowering and plant height.
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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) | 0.000 | 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".