{"id":"W2104976581","doi":"10.1109/icas.2009.17","title":"Gait Synthesis for Legged Underwater Vehicles","year":2009,"lang":"en","type":"article","venue":"","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Hexapod; Underwater; Gait; Computer science; Simulated annealing; Simulation; Marine engineering; Engineering; Robot; Artificial intelligence; Geology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003767134,0.00005914798,0.00007707273,0.00002346857,0.00002384787,0.00002177452,0.00004950861,0.00003023478,0.0001870311],"category_scores_gemma":[0.00000729916,0.00004758036,0.0000449884,0.00002444345,0.000003850828,0.00004293398,0.000001596285,0.00002358057,0.00007824424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001409081,"about_ca_system_score_gemma":0.000002209936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001139268,"about_ca_topic_score_gemma":0.000001313927,"domain_scores_codex":[0.9996942,0.00000401539,0.00007875232,0.00005896319,0.00003901432,0.0001251046],"domain_scores_gemma":[0.9998358,0.00003767068,0.000003877299,0.00008059174,0.000009827093,0.00003224941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004114279,0.0001403007,0.0001303681,0.00007892115,0.0001788906,0.000005261545,0.0002678265,0.1623515,0.07515389,0.06026211,0.06039449,0.6409954],"study_design_scores_gemma":[0.001675027,0.000102153,0.00517561,0.00003280713,0.00006866678,0.000006112713,0.0001378809,0.772745,0.1517948,0.00903371,0.05862952,0.0005987097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01185749,0.00007643191,0.9095802,0.004012396,0.0001874161,0.000319981,0.000002630585,0.0009063742,0.07305706],"genre_scores_gemma":[0.9949208,0.000004612243,0.003197958,0.0004030415,0.00005284537,0.00001798618,8.506638e-7,0.000008555235,0.00139338],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9830633,"threshold_uncertainty_score":0.2047859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070707840808686,"score_gpt":0.2029658000868511,"score_spread":0.1922587216787643,"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."}}