{"id":"W4312424509","doi":"10.1109/iros47612.2022.9981421","title":"Vehicle Type Specific Waypoint Generation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Waypoint; Probabilistic logic; Computer science; Reinforcement learning; Function (biology); Artificial intelligence; Machine learning; Real-time computing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004841229,0.0005757402,0.0004981889,0.0005723938,0.0002177891,0.0003764456,0.001819054,0.0006675776,0.003669506],"category_scores_gemma":[0.002282429,0.0004194606,0.0007564829,0.000343293,0.0004078312,0.0007647364,0.001163372,0.0008138667,0.0006951115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004226239,"about_ca_system_score_gemma":0.0007538275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001623016,"about_ca_topic_score_gemma":0.002318209,"domain_scores_codex":[0.9996313,0.00003596013,0.00001592267,0.0001200634,0.0001536934,0.00004294811],"domain_scores_gemma":[0.9993648,0.0001399677,0.00008663548,0.0002130065,0.000154995,0.00004061654],"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":[0.00008968738,0.00006446092,0.003092403,0.0000701082,0.00004608282,0.0001772269,0.00006860547,0.870473,0.01345834,0.02183049,0.001686473,0.08894309],"study_design_scores_gemma":[0.000007639449,0.00003344114,0.0003240752,0.000004930443,0.000006321281,0.00005289384,0.000006861424,0.9850295,0.006316618,0.0067259,0.001481378,0.00001036634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01525365,0.00001895812,0.9818892,0.00002765122,0.00002045113,0.00007663956,0.0001550807,0.001248388,0.001309949],"genre_scores_gemma":[0.6487777,0.00007881745,0.3458188,0.00006126415,0.0000187327,0.000264985,0.0009989287,0.0003273405,0.003653306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003669506,"threshold_uncertainty_score":0.0122757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06451494096416267,"score_gpt":0.2553018640587518,"score_spread":0.1907869230945891,"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."}}