{"id":"W2205798303","doi":"","title":"Genetic Algorithms: An Overview and Application to Power System Optimization","year":2006,"lang":"en","type":"article","venue":"","topic":"Electric Power System Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematical optimization; Electric power system; Computer science; Robustness (evolution); Genetic algorithm; Optimization problem; Nonlinear programming; Set (abstract data type); Power (physics); Nonlinear system; Algorithm; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008018954,0.0001172811,0.0001177583,0.0001055625,0.00003823439,0.00005465342,0.00006936208,0.00006437285,0.00001422162],"category_scores_gemma":[0.000002192737,0.0001218246,0.0000123168,0.0003229516,0.000004184952,0.0001451404,0.0000104867,0.00002999572,0.00002752842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001088585,"about_ca_system_score_gemma":0.000005868394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000862412,"about_ca_topic_score_gemma":0.00001906623,"domain_scores_codex":[0.9992945,0.00002103112,0.0002249119,0.0001898061,0.0001162983,0.0001534376],"domain_scores_gemma":[0.9996351,0.000008822266,0.00002297319,0.0002126788,0.00005100856,0.00006940541],"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":[7.455641e-7,0.000007307082,0.0001307683,0.00005974969,0.000004352631,5.332253e-7,0.00002732049,0.9954782,0.0003645555,0.001759175,0.0002939123,0.001873371],"study_design_scores_gemma":[0.0001118655,0.00003293928,0.001447849,0.00001967506,0.000009124355,0.0000178195,0.0000212066,0.9973541,0.0002481284,0.00001067177,0.0005743831,0.0001522529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003090858,0.001239874,0.9878989,0.00001600938,0.0001000148,0.0004440948,0.000002552248,0.0006751656,0.006532458],"genre_scores_gemma":[0.8849007,0.00004923037,0.1147033,0.00002847733,0.00006907839,0.00008979614,0.00002383974,0.0000421878,0.00009339429],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8818098,"threshold_uncertainty_score":0.4967864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005278324383300367,"score_gpt":0.2053596375371921,"score_spread":0.2000813131538918,"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."}}