{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004490018,0.0001823219,0.0003248284,0.00005571448,0.00001249685,0.00001718571,0.0001583079,0.0001262484,0.0001566054],"category_scores_gemma":[0.00005608442,0.0001842455,0.0001416204,0.00003003512,0.000009472696,0.00005234206,0.00007255808,0.0001380049,0.00001576987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485206,"about_ca_system_score_gemma":0.00003373087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006011579,"about_ca_topic_score_gemma":0.000002157806,"domain_scores_codex":[0.9987807,0.00003923371,0.0003797987,0.0001951002,0.0004722769,0.0001328749],"domain_scores_gemma":[0.9995015,0.00003967014,0.00006933657,0.0002825235,0.00004890527,0.00005805457],"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":[0.000001970626,0.00001419724,0.000002235033,0.0006636467,0.0001560235,8.920823e-8,0.0001449294,0.99219,0.001457051,0.000731313,0.00006228835,0.004576236],"study_design_scores_gemma":[0.0006674457,0.00001269902,0.00007872425,0.00008637634,0.0003692266,3.142861e-7,0.00002687842,0.9748436,0.0008802317,0.02286063,0.00001859206,0.0001553199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00335375,0.0002131346,0.9900489,0.0001202002,0.0003527295,0.001412613,0.00001109023,0.0001155229,0.004371989],"genre_scores_gemma":[0.9901687,0.00002731133,0.009166573,0.00002084969,0.00005947075,0.000406575,0.00003738724,0.00004169171,0.00007146063],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9868149,"threshold_uncertainty_score":0.7513313,"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."}}