{"id":"W2021253355","doi":"10.1142/s0219878910002142","title":"TERRAIN ROUGHNESS ASSESSMENT FOR HIGH SPEED UGV NAVIGATION IN UNKNOWN HETEROGENEOUS TERRAINS","year":2010,"lang":"en","type":"article","venue":"International Journal of Information Acquisition","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Terrain; Computer science; Traverse; Unmanned ground vehicle; Range (aeronautics); Navigation system; Standard deviation; Simulation; Real-time computing; Computer vision; Artificial intelligence; Aerospace engineering; Geodesy; Geology; Engineering; Mathematics","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":[0.000369671,0.0003457811,0.0003960181,0.0008910486,0.0002851308,0.0005469212,0.0003911354,0.000390013,0.0004138325],"category_scores_gemma":[0.002613316,0.0001755597,0.0003178962,0.0004147346,0.0002816264,0.0005632868,0.0003908309,0.0002581208,0.0001380624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004060196,"about_ca_system_score_gemma":0.0003779851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003135372,"about_ca_topic_score_gemma":0.003190675,"domain_scores_codex":[0.9996448,0.00007695463,0.00001860807,0.00005887046,0.0001567822,0.0000439952],"domain_scores_gemma":[0.9993536,0.0003000639,0.0001142307,0.00005642282,0.0001433777,0.00003224459],"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":[0.0002345984,0.00005919619,0.01858453,0.0001406495,0.00005733379,0.0002400487,0.0001374224,0.7602089,0.04230596,0.002873794,0.0006142468,0.1745434],"study_design_scores_gemma":[0.000007981536,0.00005548511,0.007323428,0.000006517112,0.00001224058,0.00007254866,0.0000458895,0.9876363,0.003558068,0.0008656335,0.0003998044,0.00001612444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2598787,0.0002148003,0.7378263,0.00005478282,0.00001502082,0.00004709846,0.0001023536,0.00039954,0.001461299],"genre_scores_gemma":[0.953051,0.0001031441,0.0463552,0.000006047681,0.00001148967,0.00002785342,0.0001388283,0.00002625062,0.0002802455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003135372,"threshold_uncertainty_score":0.006234288,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008731781000479569,"score_gpt":0.2946535627913577,"score_spread":0.2859217817908782,"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."}}