{"id":"W2081466838","doi":"10.1371/journal.pone.0002456","title":"Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms","year":2008,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":232,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institute of General Medical Sciences","keywords":"Robustness (evolution); Adaptability; Gene regulatory network; Systems biology; Organism; Boolean network; Network dynamics; Computer science; Generality; Biology; Computational biology; Biological network; Evolutionary dynamics; Gene; Genetics; Mathematics; Gene expression; Population; Ecology","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":[0.0003168463,0.0002799866,0.0002409866,0.001397433,0.0005199388,0.0007187818,0.0002944337,0.0004558937,0.001122482],"category_scores_gemma":[0.00180828,0.0001341379,0.0003072341,0.001134933,0.001178132,0.0009057614,0.0005255312,0.0003747483,0.0001177334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008575423,"about_ca_system_score_gemma":0.0002663786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002385364,"about_ca_topic_score_gemma":0.001821929,"domain_scores_codex":[0.9997862,0.00006345561,0.0000149737,0.00005210202,0.00005701555,0.00002627651],"domain_scores_gemma":[0.9992757,0.0004528453,0.00009570246,0.00003967981,0.00008020901,0.0000559129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002266691,0.00005062758,0.01722661,0.0009657184,0.00009292613,0.001533555,0.003081872,0.1227401,0.04003484,0.7353342,0.002796555,0.07591632],"study_design_scores_gemma":[0.00005559488,0.00009039737,0.0206117,0.0001650986,0.00009874434,0.001559699,0.001559088,0.2818094,0.0101098,0.6175099,0.06634879,0.00008171139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6881129,0.01457523,0.2527597,0.002361382,0.00008393203,0.0001212883,0.0005311887,0.0006319511,0.04082241],"genre_scores_gemma":[0.9657428,0.002370566,0.03064121,0.00007439643,0.00001315388,0.00004389636,0.0001622394,0.00002808084,0.0009236213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002385364,"threshold_uncertainty_score":0.00622195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03144954516924011,"score_gpt":0.2192329958183487,"score_spread":0.1877834506491086,"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."}}