{"id":"W193938319","doi":"10.1007/978-3-642-33515-0_39","title":"Velocity Selection for High-Speed UGVs in Rough Unknown Terrains Using Force Prediction","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Terrain; Base (topology); Elevation angle; Elevation (ballistics); Frame (networking); Selection (genetic algorithm); Control theory (sociology); Robot","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":[0.0003425496,0.0008325462,0.0009690971,0.0006040639,0.000627197,0.0006030748,0.0008448751,0.0007948432,0.00152969],"category_scores_gemma":[0.001039275,0.0004845453,0.0003588439,0.0005291334,0.0003725405,0.0006462409,0.0006534409,0.0006044201,0.000377288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003133953,"about_ca_system_score_gemma":0.0006099141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008213724,"about_ca_topic_score_gemma":0.006976014,"domain_scores_codex":[0.9998296,0.00003212961,0.000006619693,0.00002900521,0.00005724097,0.00004528297],"domain_scores_gemma":[0.9996124,0.0001867945,0.00003559125,0.00002573178,0.0001045128,0.0000349239],"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":[0.0002966592,0.00008520004,0.001650162,0.00007745148,0.00003483153,0.000115688,0.0000969388,0.8528558,0.008368227,0.001673333,0.001447933,0.1332977],"study_design_scores_gemma":[0.00000753138,0.00002375439,0.0002273567,0.0000026786,0.000002217607,0.000008120531,0.00001100416,0.9986745,0.0005771247,0.0003177187,0.000145591,0.000002391529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1007405,0.0003398366,0.894655,0.0001313201,0.00007292364,0.00005097259,0.00006390281,0.0006305781,0.003314885],"genre_scores_gemma":[0.9242834,0.0001311333,0.0722397,0.0000345891,0.0000432617,0.00006598062,0.0001488603,0.00006797555,0.002984962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008213724,"threshold_uncertainty_score":0.01633185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299188207622777,"score_gpt":0.2142953428900206,"score_spread":0.2013034608137928,"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."}}