Sex gene pool evolution and speciation: A new paradigm
Bibliographic record
Abstract
In this paper, we review the literature on the growing body of data demonstrating the rapid evolution of sex and reproduction related (SRR) genes and show how a paradigm shift to the study of SRR genes can provide new approaches to solving some of the old problems in evolutionary biology. The argument is based on (1) the growing scope and importance of sexual selection in evolution, (2) the growing number of case studies showing rapid evolution of sexual traits in a wide variety of taxa, (3) the faster rate of DNA sequence divergence in genes affecting sexual function and fertility, (4) the evidence for the involvement of novel traits/genes in sexual functions, and (5) a proposed sex/non-sex dichotomy of the gene pool affecting viability versus fertility. It is argued that the adoption of the sex/non-sex dichotomy of genes/traits can provide new perspectives on such problems as species concepts, modes (allopatric/sympatric) of speciation, Haldane's rule, reinforcement, and the founder effect. It is proposed that the evolutionary study of genes affecting viability versus fertility is the key to understanding the genetic basis of speciation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.003 | 0.010 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".