{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001416354,0.0006657775,0.000778413,0.002859072,0.0007904039,0.0006964238,0.0005213035,0.0004021629,0.001382169],"category_scores_gemma":[0.005629123,0.0003298969,0.0009112196,0.00219579,0.000612552,0.0007093229,0.00102795,0.0007747942,0.0001946497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006372252,"about_ca_system_score_gemma":0.0007395497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380772,"about_ca_topic_score_gemma":0.002991259,"domain_scores_codex":[0.9988987,0.0003146621,0.00006584408,0.0004235134,0.0002115971,0.00008557756],"domain_scores_gemma":[0.9948197,0.003094837,0.0007664292,0.0006564112,0.0004269855,0.0002356873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008762687,0.0003980159,0.3469073,0.003396806,0.004087016,0.002787771,0.0007511567,0.153689,0.2783017,0.04904813,0.007139907,0.1526171],"study_design_scores_gemma":[0.0001297544,0.0005316634,0.3153972,0.0001653195,0.002075747,0.002207731,0.0004565409,0.542168,0.0421473,0.07836426,0.01619726,0.000159125],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.888993,0.002010491,0.09936163,0.000204961,0.00003682529,0.0001429304,0.004864102,0.001101968,0.00328423],"genre_scores_gemma":[0.9525307,0.0004579923,0.04119148,0.0000973222,0.00001546533,0.0001419534,0.005085274,0.0001243787,0.0003555206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002859072,"threshold_uncertainty_score":0.007490516,"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."}}