{"id":"W4395671342","doi":"10.2316/j.2024.206-1087","title":"A NOVEL ROBOT PATH PLANNING ALGORITHM BASED ON THE IMPROVED WILD HORSE OPTIMISER WITH HYBRID STRATEGIES, 515-533.","year":2024,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Motion planning; Horse; Path (computing); Computer science; Robot; Algorithm; Artificial intelligence; Biology; Operating system; Paleontology","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":[0.0002876579,0.0006403176,0.0005682771,0.0005526027,0.0004344549,0.0005450085,0.001055326,0.0007891922,0.004866637],"category_scores_gemma":[0.0004704949,0.000392942,0.0004489455,0.0004653484,0.0003497066,0.0006039413,0.0006235122,0.0006800007,0.0009722715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003837621,"about_ca_system_score_gemma":0.0008548704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006415771,"about_ca_topic_score_gemma":0.0111815,"domain_scores_codex":[0.9998984,0.00001619747,0.000004798902,0.0000291371,0.00003661969,0.0000148292],"domain_scores_gemma":[0.9999193,0.00002504097,0.000007700922,0.0000107433,0.00002905538,0.000008070511],"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":[0.0002205255,0.00011331,0.0007572772,0.000129439,0.0001031712,0.0001408162,0.00008859536,0.6487447,0.01608065,0.009021778,0.005337499,0.3192623],"study_design_scores_gemma":[0.00002128078,0.00004399343,0.0001247631,0.000006448735,0.0000115467,0.00003054791,0.000009333501,0.9957986,0.001331794,0.001177506,0.001438376,0.000005767772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01668473,0.0003091568,0.9763472,0.00008549441,0.00006554302,0.00006734009,0.00008324358,0.00100053,0.005356771],"genre_scores_gemma":[0.2480073,0.0001984288,0.7395239,0.0001068174,0.00002961317,0.0001939542,0.0002988971,0.0002924742,0.01134867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006415771,"threshold_uncertainty_score":0.01628047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558472667693268,"score_gpt":0.2581194638120817,"score_spread":0.2425347371351491,"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."}}