{"id":"W2068271774","doi":"10.4161/sysb.24471","title":"Long loops of information flow in genetic networks highlight an inherent directionality","year":2013,"lang":"en","type":"article","venue":"Systems Biomedicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Directionality; Swap (finance); Computer science; Information flow; Degree distribution; Clustering coefficient; Genetic network; Flow network; Topology (electrical circuits); Enhanced Data Rates for GSM Evolution; Cluster analysis; Mathematics; Combinatorics; Gene; Complex network; Biology; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003129456,0.0001461713,0.0002663193,0.0001652048,0.00002898472,0.00001653139,0.0001452813,0.0001681233,0.00004254714],"category_scores_gemma":[0.00001756718,0.000121659,0.00005751206,0.0003752603,0.00008009982,0.00001537872,0.00004683896,0.00005821127,0.00001227152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000353861,"about_ca_system_score_gemma":0.0000379314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008606733,"about_ca_topic_score_gemma":0.0001715201,"domain_scores_codex":[0.9986527,0.0001312906,0.0005828361,0.0002030014,0.0002186751,0.0002114911],"domain_scores_gemma":[0.9990892,0.000007467334,0.0002093278,0.000399098,0.0001839295,0.0001109314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001452066,0.0004742521,0.5796426,0.0007249965,0.000683071,0.000008022993,0.0003943756,0.2071765,0.1243522,0.0000911589,0.01461657,0.07169098],"study_design_scores_gemma":[0.001363483,0.000449731,0.869377,0.0001571385,0.00007029978,0.00003376006,0.0002345241,0.1105167,0.004494377,0.0000217702,0.01292079,0.0003603805],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821599,0.002855451,0.01384244,0.00007439505,0.0004592118,0.000418614,0.000005632431,0.00001293933,0.0001714595],"genre_scores_gemma":[0.9985518,0.00009752926,0.0002107866,0.00004176199,0.0004766034,0.00006457584,0.0004039645,0.00001062453,0.0001422905],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2897344,"threshold_uncertainty_score":0.4961112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005115901732318648,"score_gpt":0.2142701046591947,"score_spread":0.2091542029268761,"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."}}