{"id":"W1985442638","doi":"10.1117/12.718411","title":"Perception and mobility research at Defence R&amp;D Canada for UGVs in complex terrain","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Terrain; Mobile robot; Computer science; Perception; Robot; Human–computer interaction; Artificial intelligence; Intelligent transportation system; Intelligent decision support system; Computer security; Engineering; Transport engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001392752,0.0002121851,0.0002804015,0.0001206087,0.00009743461,0.00005597505,0.0003747658,0.000154186,0.000009827783],"category_scores_gemma":[0.0005012389,0.0001988805,0.000162949,0.0003130052,0.0001773945,0.0002049159,0.00008759971,0.0002596003,3.92621e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006969359,"about_ca_system_score_gemma":0.00003525631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001371746,"about_ca_topic_score_gemma":0.0007918552,"domain_scores_codex":[0.9980696,2.304284e-8,0.0005784928,0.0003014559,0.000585385,0.0004650025],"domain_scores_gemma":[0.9984143,0.0002757129,0.00009128609,0.00005041288,0.00104775,0.0001205173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001454766,0.0000859564,0.002374856,0.001198194,0.0001206427,1.180272e-7,0.0006570798,0.007727786,0.8861254,0.09371017,0.007282641,0.0005716203],"study_design_scores_gemma":[0.002413518,0.0003681976,0.0441988,0.0004519391,0.00008225872,0.00002234584,0.006469697,0.8727587,0.05745632,0.002259815,0.01265579,0.0008626433],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971117,0.00005215137,0.0006791604,0.0006291638,0.0001171605,0.0006589878,0.00004607726,0.00004698159,0.0006585569],"genre_scores_gemma":[0.9479535,0.00005375665,0.05159794,0.00004385825,0.0001572566,0.0000436408,0.00002538782,0.00004652761,0.00007817151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8650309,"threshold_uncertainty_score":0.8110113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03012569986627045,"score_gpt":0.2725419409299858,"score_spread":0.2424162410637154,"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."}}