RECONCILING EXTREMELY STRONG BARRIERS WITH HIGH LEVELS OF GENE EXCHANGE IN ANNUAL SUNFLOWERS
Why this work is in the frame
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Bibliographic record
Abstract
In several cases, estimates of gene flow between species appear to be higher than we might predict given the strength of interspecific barriers separating these species pairs. However, as far as we are aware, detailed measurements of reproductive isolation have not previously been compared with a coalescent-based assessment of gene flow. Here, we contrast these two measures in two species of sunflower, Helianthus annuus and H. petiolaris. We quantified the total reproductive barrier strength between these species by compounding the contributions of the following prezygotic and postzygotic barriers: ecogeographic isolation, reproductive asynchrony, niche differentiation, pollen competition, hybrid seed formation, hybrid seed germination, hybrid fertility, and extrinsic postzygotic isolation. From this estimate, we calculated the probability that a reproductively successful hybrid is produced: estimates of P(hyb) range from 10(-4) to 10(-6) depending on the direction of the cross and the degree of independence among reproductive barriers. We then compared this probability with population genetic estimates of the per generation migration rate (m). We showed that the relatively high levels of gene flow estimated between these sunflower species (N(e) m= 0.34-0.76) are mainly due to their large effective population sizes (N(e) > 10(6)). The interspecific migration rate (m) is very small (<10(-7)) and an order of magnitude lower than that expected based on our reproductive barrier strength estimates. Thus, even high levels of reproductive isolation (>0.999) may produce genomic mosaics.
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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 it