{"id":"W3008091198","doi":"10.1534/genetics.119.302892","title":"The Temporal Dynamics of Background Selection in Nonequilibrium Populations","year":2020,"lang":"en","type":"article","venue":"Genetics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre","funders":"National Human Genome Research Institute","keywords":"Biology; Selection (genetic algorithm); Evolutionary biology; Dynamics (music); Genetics; Statistical physics; Physics; Computer science; Artificial intelligence","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":[0.001080913,0.0001419229,0.0003817631,0.0004219896,0.0005572976,0.0007894608,0.0005400453,0.0003973635,0.001021854],"category_scores_gemma":[0.004402332,0.0002163827,0.0003955456,0.0003541753,0.0009002305,0.001206705,0.0004842285,0.0007015153,0.0001183231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001245031,"about_ca_system_score_gemma":0.000563645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008030791,"about_ca_topic_score_gemma":0.007947699,"domain_scores_codex":[0.9998357,0.00006191996,0.000007350375,0.00004583202,0.00002439484,0.0000247097],"domain_scores_gemma":[0.9988594,0.0007091191,0.0001484235,0.00009747069,0.00008398412,0.0001016694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000183295,0.000133055,0.1023738,0.00008778645,0.0001706583,0.0005949067,0.001002583,0.7810602,0.0214956,0.08001173,0.001007236,0.01187917],"study_design_scores_gemma":[0.00002247167,0.00004820344,0.01927841,0.00001135208,0.00002867105,0.00008052473,0.0001857148,0.949228,0.001212826,0.0291772,0.0006952456,0.00003143174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821165,0.00007950349,0.01634938,0.0001789223,0.000006359232,0.000007701103,0.0001021894,0.00004738238,0.001112045],"genre_scores_gemma":[0.9975606,0.00006064976,0.00196316,0.00002734043,0.000002003379,0.00001497212,0.00007956644,0.00000949492,0.0002820948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008030791,"threshold_uncertainty_score":0.01596814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02430713406479532,"score_gpt":0.2740791973969733,"score_spread":0.249772063332178,"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."}}