A novel approach to estimating the cost of male fertility restoration in gynodioecious plants
Bibliographic record
Abstract
*In many gynodioecious plants, sex is determined by cytoplasmic male sterility genes (CMS) and nuclear male fertility restorers (Rf). Models predict that the costs of restoration are important determinants of population sex ratios. However, current approaches to the estimation of these costs require prior identification of CMS genotypes, information that is available for few species. *We tested a novel approach to estimating the cost of restoration in natural populations without determining CMS or Rf genotypes. We used estimates of pollen viability and offspring sex ratios from open- and hand-pollinated families of Lobelia siphilitica to test whether the cost of restoration, expressed as low pollen viability, is higher in populations with more females. *Among populations with CMS, we found that variation in pollen viability was higher in small populations with more females, as expected if the proportion of females within populations increases with the maximum cost of restoration. In controlled crosses, families with low pollen viability also produced fewer females, suggesting that variation in viability is primarily determined by the number and frequency of Rf alleles carried. *This approach to estimating the cost of restoration can be applied to other cytonuclear gynodioecious species, offering new opportunities for testing gynodioecy models in the wild.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".