{"id":"W2156871280","doi":"10.1186/gb-2007-8-8-r160","title":"Network motif analysis of a multi-mode genetic-interaction network","year":2007,"lang":"en","type":"article","venue":"Genome Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institutes of Health; Michael Smith Health Research BC; University of Washington","keywords":"Motif (music); Genetic network; Computer science; Computational biology; Interaction network; Mode (computer interface); Software; Network motif; Gene; Artificial intelligence; Biological network; Data mining; Biology; Genetics; Human–computer interaction; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005087083,0.0002059893,0.0003891188,0.0001230875,0.0000894608,0.00001030778,0.000265735,0.0003555265,0.00006277332],"category_scores_gemma":[0.00001808597,0.0001954722,0.0002510563,0.0004705318,0.0001154045,0.000002731345,0.0001676873,0.0001271795,0.00001381193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002301228,"about_ca_system_score_gemma":0.00003444702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004996122,"about_ca_topic_score_gemma":0.000497066,"domain_scores_codex":[0.998327,0.00006112907,0.0006098637,0.000342789,0.00006117421,0.0005980261],"domain_scores_gemma":[0.9989568,0.00003380206,0.0003162249,0.0004831406,0.00009945254,0.0001105893],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000797288,0.0002497903,0.1288203,0.0000441894,0.005087247,0.000008294123,0.0003607283,0.4810345,0.3412499,0.001773159,0.002974066,0.03760045],"study_design_scores_gemma":[0.003041931,0.002078529,0.6189694,0.00003214173,0.00252319,0.00006559717,0.0003339091,0.0713258,0.005193035,0.003105039,0.291301,0.002030398],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5895663,0.002575803,0.4055974,0.00003061066,0.0006405688,0.0002268067,0.00005068906,0.00001703026,0.001294829],"genre_scores_gemma":[0.9803465,0.0002252189,0.01711349,0.000444425,0.000981256,0.000007462014,0.0006692291,0.00001987921,0.0001925563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4901491,"threshold_uncertainty_score":0.7971123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223051076502719,"score_gpt":0.2724488565102989,"score_spread":0.2602183457452717,"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."}}