{"id":"W4207051450","doi":"10.32920/16838284.v1","title":"Novel Methods In Training Autonomous Vehicles For Urban Roads","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Pedestrian; Brake; Computer science; Training (meteorology); Reinforcement learning; Virtual reality; Control (management); Simulation; Human–computer interaction; Transport engineering; Automotive engineering; Engineering; Artificial intelligence","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":[0.0007647754,0.0006738286,0.0005010632,0.0004222937,0.0002911116,0.0007794125,0.001079882,0.0009992546,0.003047014],"category_scores_gemma":[0.002452401,0.0005358068,0.0004729457,0.0004136202,0.0007051593,0.0008018861,0.0009597844,0.001065848,0.0006765804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000649251,"about_ca_system_score_gemma":0.0006691693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005451645,"about_ca_topic_score_gemma":0.005227617,"domain_scores_codex":[0.9997166,0.00007175022,0.00001376516,0.0001000585,0.00006690739,0.00003085156],"domain_scores_gemma":[0.9993867,0.0003435927,0.00006127074,0.00006382175,0.0001133895,0.00003121981],"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":[0.00004244882,0.00003824256,0.0007775534,0.0001117614,0.00004654374,0.00005098222,0.0000768588,0.864804,0.002902881,0.01817016,0.002191173,0.1107875],"study_design_scores_gemma":[0.000004287703,0.00001374519,0.00008618179,0.000008232661,0.000002456514,0.000009898979,0.000007759008,0.9931316,0.0005374739,0.005064115,0.001131951,0.000002375675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01924501,0.00103598,0.9735882,0.0004084672,0.0001417224,0.00005254939,0.00009681197,0.0006855592,0.00474581],"genre_scores_gemma":[0.5807492,0.001020065,0.3988758,0.0003688386,0.0002327377,0.0002803092,0.0004803748,0.0003045511,0.01768816],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005451645,"threshold_uncertainty_score":0.01083982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04555888212453215,"score_gpt":0.29728288223616,"score_spread":0.2517240001116279,"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."}}