{"id":"W2999073106","doi":"10.5539/cis.v13n1p41","title":"Artificial God Optimization - A Creation","year":2020,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Particle swarm optimization; Computer science; Field (mathematics); Multi-swarm optimization; Benchmark (surveying); Swarm intelligence; Metaheuristic; Optimization problem; Genetic algorithm; Mathematical optimization; Simple (philosophy); Artificial intelligence; Derivative-free optimization; Focus (optics); Algorithm; Machine learning; Mathematics; Physics; Epistemology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001134092,0.0006097717,0.000784657,0.0008518398,0.0007924599,0.002343606,0.0009599179,0.001054101,0.003772762],"category_scores_gemma":[0.002164257,0.0003057101,0.0009434848,0.001104874,0.001744514,0.001991054,0.002174025,0.00199633,0.001132734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006377717,"about_ca_system_score_gemma":0.001384491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007369808,"about_ca_topic_score_gemma":0.0007348547,"domain_scores_codex":[0.9991679,0.0002497963,0.00003938179,0.0001356894,0.0003600465,0.00004717776],"domain_scores_gemma":[0.9993943,0.0002268496,0.00006241506,0.0001105712,0.0001382563,0.00006761755],"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":[0.00009723547,0.00006816244,0.001565934,0.0006955232,0.0001318617,0.0002772412,0.0004256847,0.07158738,0.005289082,0.6241549,0.02901739,0.2666896],"study_design_scores_gemma":[0.00006019599,0.0001839893,0.0009153312,0.000297131,0.00006234003,0.0006926063,0.0001811079,0.2287093,0.006006858,0.2560509,0.5067441,0.0000960962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01359606,0.01764448,0.8475696,0.005081234,0.001888354,0.0001761633,0.0002840339,0.001311427,0.1124487],"genre_scores_gemma":[0.2877305,0.0198132,0.6407497,0.002003571,0.001017381,0.0004200625,0.0006519037,0.0006564874,0.0469572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003772762,"threshold_uncertainty_score":0.01262116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02813909735041816,"score_gpt":0.277713342972343,"score_spread":0.2495742456219248,"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."}}