{"id":"W1996973085","doi":"10.3389/fgene.2013.00290","title":"Genetic interaction networks: better understand to better predict","year":2013,"lang":"en","type":"review","venue":"Frontiers in Genetics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":121,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Multicellular organism; Biology; In silico; Gene; Computational biology; Robustness (evolution); Genome; Function (biology); Caenorhabditis elegans; Genetics; Model organism; Phenotype; Epistasis; Biological network; Systems biology","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":[0.003192122,0.002760298,0.002489617,0.005445041,0.000600638,0.004316741,0.002334884,0.002188197,0.004689118],"category_scores_gemma":[0.01136505,0.001257367,0.001966161,0.003412725,0.001778557,0.009639855,0.002320751,0.003965561,0.001904357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001651226,"about_ca_system_score_gemma":0.001625311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004445952,"about_ca_topic_score_gemma":0.003035559,"domain_scores_codex":[0.9980673,0.0007258112,0.0001605984,0.0005610933,0.0003965829,0.00008857053],"domain_scores_gemma":[0.9943499,0.0037294,0.0007320455,0.000523674,0.0004871687,0.0001778211],"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":[0.000272966,0.000208394,0.02525621,0.008023154,0.001762874,0.0009100343,0.0006876863,0.265672,0.01611899,0.2676753,0.04342091,0.3699916],"study_design_scores_gemma":[0.00003387223,0.00007628298,0.004904131,0.0007903786,0.0003139118,0.000547211,0.0002754974,0.3407317,0.003988472,0.5332801,0.114904,0.000154373],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01449224,0.0485335,0.9052153,0.01097771,0.000519439,0.0001815429,0.009729701,0.004230426,0.006120111],"genre_scores_gemma":[0.1989764,0.08813794,0.6774772,0.003079869,0.001262203,0.0007200264,0.02457688,0.0013698,0.004399661],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005445041,"threshold_uncertainty_score":0.01688176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01679216468991866,"score_gpt":0.2603267439324231,"score_spread":0.2435345792425044,"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."}}