{"id":"W2898354798","doi":"10.1002/rob.21833","title":"Data‐driven mobility risk prediction for planetary rovers","year":2018,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Soil Mechanics and Vehicle Dynamics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Shared Services Canada; Concordia University","funders":"Canadian Space Agency","keywords":"Slip (aerodynamics); Predictability; Terrain; Computer science; Mobility model; Geology; Engineering; Mathematics; Distributed computing; Aerospace engineering; Geography; Statistics","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":[0.0002329323,0.0000649988,0.0001191054,0.00003763902,0.00004134937,0.00001606517,0.0002136892,0.00009048254,0.00001168518],"category_scores_gemma":[0.0001144771,0.00005920205,0.00004574119,0.000039647,0.000009733197,0.0001329331,0.00002545032,0.000203108,0.00000192538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002502046,"about_ca_system_score_gemma":0.00001785668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005457774,"about_ca_topic_score_gemma":0.00003483205,"domain_scores_codex":[0.9994581,0.00000895835,0.0002567977,0.00006545864,0.0001007092,0.0001099769],"domain_scores_gemma":[0.9994202,0.0001113977,0.00009207922,0.0002311451,0.00008980915,0.0000554292],"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":[0.0001506691,0.00008890562,0.01056599,0.0001267785,0.0003644932,0.00001028214,0.0002038591,0.8922347,0.0003153547,0.0004080957,0.03964594,0.05588488],"study_design_scores_gemma":[0.000283742,0.0003620827,0.001519065,0.00001913503,0.00007167393,0.00001707256,0.00003687161,0.9948404,0.0001091944,0.0004765151,0.002206471,0.00005771812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.241858,0.0001717097,0.7519697,0.0002349237,0.004799332,0.0001658047,0.0003786524,0.00005866458,0.000363225],"genre_scores_gemma":[0.9805031,0.0003441865,0.01802283,0.00005850853,0.001023481,4.498328e-7,0.00002359163,0.00001377389,0.00001012724],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.738645,"threshold_uncertainty_score":0.2414189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081335526796194,"score_gpt":0.2444084943999739,"score_spread":0.2235951391320119,"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."}}