{"id":"W2588680506","doi":"10.1111/nph.14410","title":"What can genome‐wide association studies tell us about the evolutionary forces maintaining genetic variation for quantitative traits?","year":2017,"lang":"en","type":"review","venue":"New Phytologist","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Division of Integrative Organismal Systems; National Science Foundation","keywords":"Genetic architecture; Biology; Selection (genetic algorithm); Genome-wide association study; Genetic variation; Evolutionary biology; Variation (astronomy); Adaptation (eye); Balancing selection; Genetic association; Population; Human evolutionary genetics; Quantitative trait locus; Genome; Genetics; Machine learning; Gene; Genotype; Single-nucleotide polymorphism; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004301407,0.000956782,0.002454106,0.003301322,0.0004068936,0.001852732,0.00168266,0.002793469,0.00324765],"category_scores_gemma":[0.008524992,0.0004570092,0.001190389,0.002705609,0.001678208,0.003204138,0.000835261,0.003229071,0.001748054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169514,"about_ca_system_score_gemma":0.002298246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001719075,"about_ca_topic_score_gemma":0.002085972,"domain_scores_codex":[0.9993556,0.0001806433,0.0001007583,0.0001499092,0.0001714044,0.00004158518],"domain_scores_gemma":[0.9935372,0.004927001,0.0003618594,0.0001634863,0.0007846101,0.0002257549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001269928,0.00003518558,0.0008943558,0.02343108,0.0004946071,0.0002717843,0.0001165406,0.0003389498,0.0009623074,0.01194944,0.04289971,0.918479],"study_design_scores_gemma":[0.00003382867,0.0001016506,0.004165149,0.0175669,0.0006575667,0.001348375,0.0002008141,0.0001817387,0.0004315563,0.0260357,0.9491814,0.00009539327],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00005594642,0.9965743,0.0002078896,0.002186085,0.0005573604,0.000003248547,0.00003636537,0.000005444631,0.0003734212],"genre_scores_gemma":[0.0004543199,0.9977021,0.0002468469,0.0008037812,0.0005843312,0.000007532438,0.00003725339,0.000002159743,0.0001618014],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004301407,"threshold_uncertainty_score":0.02274835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08858083439729635,"score_gpt":0.3651673537767838,"score_spread":0.2765865193794875,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}