{"id":"W2621359109","doi":"10.25088/complexsystems.15.3.183","title":"Evolving Distributed Control for an Object Clustering Task","year":2005,"lang":"en","type":"article","venue":"Complex Systems","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Air Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Task (project management); Cluster analysis; Computer science; Scaling; Key (lock); Object (grammar); Population; Control (management); Distributed computing; Genetic algorithm; Sensitivity (control systems); Constant (computer programming); Robot; Cluster (spacecraft); Artificial intelligence; Machine learning; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0008981216,0.0005342344,0.0005447743,0.0003140072,0.0005669968,0.0007736963,0.0008418846,0.0009918115,0.001407842],"category_scores_gemma":[0.002202612,0.0002164444,0.0003167396,0.0003228142,0.00080216,0.0006225772,0.001085101,0.0006907389,0.0001448321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007683972,"about_ca_system_score_gemma":0.0005101339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003315163,"about_ca_topic_score_gemma":0.002054721,"domain_scores_codex":[0.9997781,0.0000498472,0.000008982636,0.00006943537,0.000050076,0.00004363959],"domain_scores_gemma":[0.999253,0.0004058458,0.00009858081,0.00007561798,0.00009990202,0.00006693941],"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":[0.00007673199,0.00006822772,0.000403798,0.00003363906,0.00002450959,0.00009445364,0.0001377724,0.9575352,0.007741421,0.009375582,0.000420448,0.0240881],"study_design_scores_gemma":[0.00001844459,0.00004510191,0.00009722059,0.000002104182,0.000004866489,0.00001421861,0.00001952469,0.996228,0.0009976755,0.00230018,0.0002687215,0.000003976005],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3008165,0.0002203869,0.6901591,0.0003966023,0.00004687952,0.00008126454,0.00002564688,0.000353252,0.007900406],"genre_scores_gemma":[0.9560867,0.00005819006,0.04104586,0.00005542277,0.00001240691,0.00007259718,0.00002573525,0.00003008522,0.002612988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003315163,"threshold_uncertainty_score":0.006591737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03583827998495839,"score_gpt":0.277652793157831,"score_spread":0.2418145131728726,"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."}}