OPPOSING LEVELS OF SELECTION CAN CAUSE NEUTRALITY: MATING PATTERNS AND MATERNAL-FETAL INTERACTIONS
Bibliographic record
Abstract
A biallelic viability model based on human data for maternal-fetal interactions reported by Hedrick (1997) gives the interesting result of neutral stability at all gene frequencies. I show that there are two levels of selection, within and among families, acting in opposing directions in this model and that the neutral stability occurs when the two levels of selection exactly balance one another, as they do in a randomly mating population. Deviations from random mating disrupt the balance and consequently destroy the neutral stability. However, with inbreeding avoidance, which characterizes the human histocompatibility loci, within-family selection is strengthened and among-family selection is weakened. This favors the invasion of new alleles and contributes to a high equilibrium level of genetic diversity at loci with maternal-fetal interactions affecting offspring viability in the pattern described by Hedrick. This pattern of selection is remarkably similar to that observed for the maternal effect selfish genes, Medea in flour beetles and scat in the mouse, and the Gp-9 gene in the fire ant.Corresponding Editor: T. Markow
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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) | 0.001 | 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 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".