{"id":"W2799762305","doi":"10.1126/science.aao1729","title":"Systematic analysis of complex genetic interactions","year":2018,"lang":"en","type":"article","venue":"Science","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":314,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; University of Minnesota; Canton de Genève; National Human Genome Research Institute; University of Toronto; National Institutes of Health; National Science Foundation","keywords":"Biology; Genetics; Gene; Inheritance (genetic algorithm); Mutant; Phenotype; Epistasis; Gene interaction; Genetic analysis; Mutation; Interaction network; Computational biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002297012,0.00004668613,0.0001156022,0.0001207936,0.0001064701,0.00001960447,0.0002574608,0.00001819801,0.00004080453],"category_scores_gemma":[0.0000467304,0.00003832221,0.00005927987,0.000655006,0.0004971735,0.000003069427,0.00008890044,0.00001871988,0.00001375563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007213485,"about_ca_system_score_gemma":0.00004561891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000534,"about_ca_topic_score_gemma":0.00004906323,"domain_scores_codex":[0.9994348,0.00001095527,0.0002014655,0.0001241344,0.000107249,0.0001213813],"domain_scores_gemma":[0.9993926,0.00000726589,0.0001035306,0.0003131748,0.0001404301,0.0000429414],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001100747,0.00004181713,0.001874178,0.0003324833,0.0004258665,2.646283e-7,0.0004338185,0.0006916501,0.9936109,0.0005729078,0.0007176187,0.001287441],"study_design_scores_gemma":[0.0006176461,0.001028015,0.2110904,0.0006015172,0.001946531,0.0000472728,0.001301834,0.5980936,0.1746315,0.0009018516,0.00885337,0.0008865306],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9477331,0.0001578181,0.04380385,0.00003270343,0.0002844101,0.0001574204,0.0000117211,0.000005696344,0.007813265],"genre_scores_gemma":[0.9967432,0.000006842432,0.002888245,0.00009844809,0.00004747278,0.000003104769,0.000006403337,0.000002002902,0.0002042549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8189794,"threshold_uncertainty_score":0.1831856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01352636086109628,"score_gpt":0.2826508513467141,"score_spread":0.2691244904856178,"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."}}