{"id":"W2137112190","doi":"10.1093/bioinformatics/btm004","title":"SGN Sim, a Stochastic Genetic Networks Simulator","year":2007,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Set (abstract data type); Gene regulatory network; Stochastic simulation; Master regulator; Translation (biology); Stochastic modelling; Stochastic process; Simulation; Algorithm; Theoretical computer science; Gene; Transcription factor; Genetics; Mathematics; Gene expression; Programming language; Biology; Messenger RNA","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":[0.0003576561,0.0002491555,0.0002167771,0.00009896496,0.0001233533,0.00004130298,0.000286058,0.0002493687,0.00003085533],"category_scores_gemma":[0.00006571206,0.0002392514,0.0001822809,0.0002716641,0.00009068366,0.000006110005,0.0001492745,0.0001090176,0.00006815102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003035735,"about_ca_system_score_gemma":0.00006184615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000030253,"about_ca_topic_score_gemma":0.00002610797,"domain_scores_codex":[0.9984131,0.0000198915,0.0005573303,0.0002150109,0.0002430856,0.000551528],"domain_scores_gemma":[0.9988045,0.00002863214,0.0001919764,0.0006318422,0.0001120154,0.0002310643],"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":[0.0000848472,0.00008329745,0.002713924,0.00003921,0.0002579527,0.000007239798,0.0001207814,0.9693455,0.002382574,0.00005847092,0.004822282,0.02008392],"study_design_scores_gemma":[0.0009418592,0.0003569929,0.008397883,0.00002543734,0.0001765771,0.0000577278,0.0002388403,0.9656882,0.002713936,0.00004358695,0.02059574,0.0007632389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.389666,0.0008433608,0.6084004,0.00001407479,0.0002126159,0.0001986789,0.000004499202,0.00003689326,0.0006234203],"genre_scores_gemma":[0.9880878,0.0000336396,0.01046136,0.0003358359,0.0005806698,0.000005252143,0.00007072702,0.00003508203,0.0003896378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5984218,"threshold_uncertainty_score":0.9756387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006631584881200314,"score_gpt":0.2278340997158765,"score_spread":0.2212025148346762,"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."}}