{"id":"W2093641157","doi":"10.1109/aero.2011.5747270","title":"Path planning on a network of paths","year":2011,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Terrain; Motion planning; Computer science; Mobile robot; Path (computing); Global Positioning System; Mobile robot navigation; Robot; Real-time computing; Artificial intelligence; Work (physics); Computer vision; Human–computer interaction; Engineering; Computer network; Robot control; Telecommunications; Geography","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":[0.0002537987,0.00009285346,0.0001367991,0.00003443125,0.00004147909,0.00001386739,0.0005868796,0.00004229607,0.00001907749],"category_scores_gemma":[0.0000269893,0.00007510125,0.00003742694,0.0002265713,0.00002056474,0.0001157668,0.0001201471,0.00009047178,0.00006172219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000101156,"about_ca_system_score_gemma":0.00003944133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002324934,"about_ca_topic_score_gemma":6.420233e-8,"domain_scores_codex":[0.9991208,0.00003745233,0.000176662,0.0002244598,0.0001913461,0.0002493],"domain_scores_gemma":[0.9992813,0.00007733872,0.00008366955,0.0004572011,0.00003538622,0.00006506505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006167697,0.0006156214,0.09160824,0.00006985693,0.000128197,0.0008820199,0.02597343,0.03882832,0.0002914493,0.7082735,0.04918309,0.08408465],"study_design_scores_gemma":[0.001170141,0.002097407,0.25764,0.0007448833,0.00001907608,0.00009372944,0.0002367797,0.7013652,0.005080878,0.02905563,0.001466166,0.001030086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005926229,0.00004934912,0.9030489,0.00002574749,0.0004341288,0.0000650985,4.710785e-7,0.0001830603,0.09026696],"genre_scores_gemma":[0.4249375,8.930242e-7,0.5745764,0.0002125159,0.00005129442,0.000003216616,4.161099e-7,0.000005121021,0.0002126792],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6792178,"threshold_uncertainty_score":0.306254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05973637401649006,"score_gpt":0.251306565003944,"score_spread":0.191570190987454,"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."}}