Predicting evolution of floral traits associated with mating system in a natural plant population
Bibliographic record
Abstract
Evolution of floral traits requires that they are heritable, that they affect fitness, and that they are not constrained by genetic correlations. These prerequisites have only rarely been examined in natural populations. For Mimulus guttatus, we found by using the Riska-method that corolla width, anther length, ovary length and number of red dots on the corolla were heritable in a natural population. Seed production (maternal fitness) was directly positively affected by corolla width and anther size, and indirectly so by ovary length and number of red dots on the corolla. The siring success (paternal fitness), as estimated from allozyme data, was directly negatively affected by anther-stigma separation, and indirectly so by the corolla length-width ratio. Genetic correlations, estimated with the Lynch-method, were positive between floral size measures. We predict that larger flowers with larger reproductive organs, which generally favour outcrossing, will evolve in this natural population of M. guttatus.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".