Heterosis increases the effective migration rate
Why this work is in the frame
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Bibliographic record
Abstract
Individuals coming from the same subpopulation are more likely to share deleterious mutations at any given locus than hybrids formed between parents from different populations. Offspring of migrants therefore may experience heterosis and have higher fitness than resident individuals. This will, in turn, result in the immigrant alleles being present in higher frequencies than predicted from neutral expectations and thus a higher effective migration rate. In this paper we derive a formula to calculate the effective migration rate in the presence of heterosis. It is shown that the effect of heterosis on the migration rate can be substantial when fitness reduction within local populations is severe. The effect will be more pronounced in species with relatively short map lengths. Furthermore the heterosis effect will be highly variable throughout the genome, with the largest effect seen near selected genes and in regions of high gene density.
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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 | 0.001 | 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 | 0.001 |
| 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