{"id":"W3015435304","doi":"10.1109/crv50864.2020.00034","title":"Evaluation of Skid-Steering Kinematic Models for Subarctic Environments","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Robotic Locomotion and Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Center for Northern Studies","funders":"","keywords":"Odometry; Skid (aerodynamics); Terrain; Robot; Kinematics; Robustness (evolution); Snow; Computer science; Subarctic climate; Motion planning; Mobile robot; Simulation; Artificial intelligence; Engineering; Meteorology; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009724865,0.001017305,0.0006362682,0.0005966352,0.0003402259,0.0007016138,0.0006573901,0.0007529186,0.0009986217],"category_scores_gemma":[0.003485335,0.0004685107,0.0005000429,0.0004283062,0.0004038321,0.0005242412,0.0005295749,0.0005490624,0.0003796523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008198395,"about_ca_system_score_gemma":0.0009364617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04406909,"about_ca_topic_score_gemma":0.0355932,"domain_scores_codex":[0.9995984,0.0001118378,0.00003569889,0.00008116855,0.0001076514,0.00006526618],"domain_scores_gemma":[0.9983973,0.0007714508,0.0001984472,0.0001774689,0.000371182,0.00008419061],"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":[0.0000726738,0.00003921901,0.002930696,0.00005020744,0.00002489332,0.00002091599,0.00002595672,0.98996,0.0006994749,0.0001284698,0.00009779861,0.005949728],"study_design_scores_gemma":[0.00001072735,0.00007653562,0.002005956,0.00001114936,0.000009936439,0.00001260913,0.00002727752,0.9966872,0.0008313876,0.00007408825,0.0002467549,0.000006340886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.917326,0.0004391008,0.07581961,0.0001799582,0.00004024443,0.00008614019,0.001015118,0.001362957,0.003730803],"genre_scores_gemma":[0.9925715,0.00008896826,0.006400326,0.00001101305,0.000002635911,0.00002165569,0.0004805489,0.00002231339,0.0004010194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04406909,"threshold_uncertainty_score":0.08762515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07206280686516038,"score_gpt":0.2668531635910191,"score_spread":0.1947903567258588,"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."}}