{"id":"W2128247685","doi":"10.1109/icsmc.1995.537808","title":"Robot path planning using genetic algorithms","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Motion planning; Computer science; Genetic algorithm; Path (computing); Robot; Artificial intelligence; Algorithm; Machine learning; Computer network","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":[0.0001639016,0.0002089586,0.0002068616,0.0001435259,0.0001965625,0.0002118146,0.0009259644,0.00008394357,0.00008830045],"category_scores_gemma":[0.0000315651,0.0001934783,0.00006419366,0.0004690875,0.00003670387,0.0003835359,0.0002485868,0.0001765365,0.000275796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005839006,"about_ca_system_score_gemma":0.00002195211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000411135,"about_ca_topic_score_gemma":5.229773e-8,"domain_scores_codex":[0.9981806,0.00006265132,0.0002901487,0.0005260541,0.0003982898,0.0005422274],"domain_scores_gemma":[0.9989277,0.0000775315,0.00009056854,0.0006745952,0.00005184839,0.0001777608],"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":[0.000001594586,0.0002289036,0.006683312,0.00002742938,0.000076523,0.001694675,0.003732586,0.7524139,0.002576595,0.001906876,0.008055774,0.2226018],"study_design_scores_gemma":[0.0002097405,0.00004863813,0.00401989,0.00003462741,0.000005843347,0.0002759771,0.0000218006,0.994188,0.0002497472,0.0002277007,0.0004401535,0.0002779474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002903675,0.0005414033,0.9909647,0.0001734019,0.000633704,0.0001056208,7.815568e-7,0.0004818357,0.004194894],"genre_scores_gemma":[0.05995094,0.000006063175,0.9387193,0.0003456115,0.0001624965,0.000004493265,6.400901e-7,0.00001744921,0.0007930385],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.241774,"threshold_uncertainty_score":0.7889817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07233880266214743,"score_gpt":0.2767000770325934,"score_spread":0.204361274370446,"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."}}