Bibliographic record
Abstract
Patterns and risks of human disease have evolved. In this article, I review evidence regarding the importance of recent adaptive evolution, positive selection, and genomic conflicts in shaping the genetic and phenotypic architectures of polygenic human diseases. Strong recent selection in human populations can create and maintain genetically based disease risk primarily through three processes: increased scope for dysregulation from recent human adaptations, divergent optima generated by intraspecific genomic conflicts, and transient or stable deleterious by-products of positive selection caused by antagonistic pleiotropy, ultimately due to trade-offs at the levels of molecular genetics, development, and physiology. Human disease due to these processes appears to be concentrated in three sets of phenotypes: cognition and emotion, reproductive traits, and life-history traits related to long life-span. Diverse, convergent lines of evidence suggest that a small set of tissues whose pleiotropic patterns of gene function and expression are under especially strong selection-brain, placenta, testis, prostate, breast, and ovary-has mediated a considerable proportion of disease risk in modern humans.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".