{"id":"W2030990090","doi":"10.1109/isb.2012.6314134","title":"New global stability conditions for genetic regulatory networks with time-varying delays","year":2012,"lang":"en","type":"article","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Stability (learning theory); Linear matrix inequality; Lyapunov function; Function (biology); Control theory (sociology); Computer science; Matrix (chemical analysis); Gene regulatory network; Genetic algorithm; Mathematical optimization; Mathematics; Gene; Nonlinear system; Control (management); Biology; Genetics; Artificial intelligence; Physics","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":[0.001081948,0.001003926,0.0005088681,0.0009767658,0.0003841025,0.0007722751,0.0005349921,0.0007420923,0.002999568],"category_scores_gemma":[0.00251833,0.0002531723,0.0006194911,0.0004112265,0.001166462,0.001080928,0.0007364622,0.0009832222,0.000362136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001052018,"about_ca_system_score_gemma":0.0007592844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001176851,"about_ca_topic_score_gemma":0.001587018,"domain_scores_codex":[0.9995055,0.00009810073,0.00002531024,0.0001590573,0.0001586041,0.00005344653],"domain_scores_gemma":[0.9987592,0.0006501116,0.0002067683,0.00003673258,0.0003006053,0.00004651758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001189109,0.00004318267,0.0006445103,0.0002501268,0.00005199488,0.0005974136,0.000548922,0.5765721,0.06025203,0.3314906,0.002087214,0.027343],"study_design_scores_gemma":[0.00002461176,0.00008182752,0.0003802871,0.00002799713,0.00002041729,0.00008512221,0.00006866067,0.9220222,0.005240621,0.06895556,0.003068296,0.00002443162],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02770549,0.0005517163,0.9629408,0.0002204437,0.00005171039,0.00005787038,0.0000979008,0.0001524387,0.008221588],"genre_scores_gemma":[0.9147394,0.001194592,0.07565072,0.0001665147,0.00008587101,0.0004036365,0.0001960986,0.00009395392,0.007469268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002999568,"threshold_uncertainty_score":0.01003456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008877458780960657,"score_gpt":0.2341383129952532,"score_spread":0.2252608542142926,"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."}}