{"id":"W3043512511","doi":"10.1177/1548512920937077","title":"Layout optimization of a military operations center using a genetic algorithm","year":2020,"lang":"en","type":"article","venue":"The Journal of Defense Modeling and Simulation Applications Methodology Technology","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Genetic algorithm; Swap (finance); Fitness function; Representation (politics); Encoding (memory); Process (computing); Algorithm; Selection (genetic algorithm); String (physics); Mathematical optimization; Artificial intelligence; Machine learning; Mathematics","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":[0.0003010773,0.0001017952,0.0002275123,0.0001979138,0.0001053221,0.000003065486,0.0001308105,0.000132716,0.000004189421],"category_scores_gemma":[0.0001663488,0.00008470575,0.00003438879,0.000263211,0.00009658702,0.00006181267,0.00003037074,0.0002167723,3.703403e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001933287,"about_ca_system_score_gemma":0.0000174462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003958253,"about_ca_topic_score_gemma":6.065515e-7,"domain_scores_codex":[0.9991202,0.0001217188,0.0004937809,0.00009138959,0.00007219126,0.0001007622],"domain_scores_gemma":[0.9992914,0.0001923257,0.00008807265,0.0001507781,0.0002381668,0.00003924481],"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":[0.00001502734,0.00001086695,0.00001165751,0.00001475976,0.00003320177,3.060501e-7,0.0003714182,0.9932701,0.0004340859,0.0001194904,0.00000110451,0.005717987],"study_design_scores_gemma":[0.0002753275,0.00004612884,0.000002561456,0.000008535097,0.00008750072,0.00004981942,0.000241193,0.9972615,0.0002924902,0.00162524,0.00003986032,0.00006986119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02800714,0.001383089,0.9700268,0.0002826339,0.00004934438,0.0001670172,0.000008338434,0.00006912177,0.00000653308],"genre_scores_gemma":[0.4574221,0.0003940394,0.5421011,0.00003071165,0.00003459943,0.000003264628,0.000002954248,0.00001067527,5.042354e-7],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.429415,"threshold_uncertainty_score":0.34542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07347129675265664,"score_gpt":0.3122430090256722,"score_spread":0.2387717122730156,"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."}}