{"id":"W2061854785","doi":"10.1038/srep04819","title":"Transittability of complex networks and its applications to regulatory biomolecular networks","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Program for New Century Excellent Talents in University; Japan Society for the Promotion of Science; Council for Science and Technology Policy; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Controllability; Computer science; Complex network; Graph; Set (abstract data type); Kernel (algebra); Complex system; State (computer science); Biological network; Topology (electrical circuits); Theoretical computer science; Distributed computing; Algorithm; Mathematics; Artificial intelligence; Bioinformatics; 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":[0.001358712,0.0001631514,0.0002477043,0.00008662567,0.0001962029,0.00004639347,0.0001630923,0.0001357727,0.00001752675],"category_scores_gemma":[0.00005223014,0.000165276,0.0001377998,0.0005076826,0.00023732,0.000004173765,0.000124618,0.00005461928,0.000001524728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001079479,"about_ca_system_score_gemma":0.00004191374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003829023,"about_ca_topic_score_gemma":0.00002685171,"domain_scores_codex":[0.9979913,0.0001047217,0.0004876825,0.0008896395,0.0002386282,0.0002880786],"domain_scores_gemma":[0.9980662,0.00001226029,0.00020646,0.001249217,0.0002435228,0.0002223759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001997657,0.00009098561,0.008683341,0.00004077607,0.0001026577,0.000003946619,0.00003798854,0.1061451,0.8722257,0.0001623268,0.004149073,0.00833815],"study_design_scores_gemma":[0.0005881769,0.0003273694,0.06248639,0.00005907231,0.000390612,0.0002296173,0.00006523295,0.165328,0.3643737,0.002200124,0.4025913,0.001360396],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7616835,0.001135814,0.2361283,0.00005979231,0.0003604231,0.0004205928,0.000001666408,0.00001731506,0.000192573],"genre_scores_gemma":[0.9986342,0.00001212633,0.0006757174,0.00006475414,0.0001520922,0.00004309577,0.0001383591,0.00001920987,0.0002604734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.507852,"threshold_uncertainty_score":0.6739761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009837347896152477,"score_gpt":0.2399736184766629,"score_spread":0.2301362705805104,"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."}}