{"id":"W4393253057","doi":"10.1109/tits.2024.3373531","title":"A Driver-Vehicle Model for ADS Scenario-Based Testing","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Exploratory Research for Advanced Technology; Japan Science and Technology Agency; Gran Sasso Science Institute; Natural Sciences and Engineering Research Council of Canada; Knut och Alice Wallenbergs Stiftelse","keywords":"Computer science; Vehicle safety; Automotive engineering; Simulation; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001715289,0.0002470767,0.0002304183,0.0002945708,0.0001709139,0.00005684497,0.0001291651,0.000246044,0.0000235822],"category_scores_gemma":[0.000001766336,0.0002589186,0.0001835833,0.0004022984,0.00004935966,0.0001596985,7.77051e-8,0.0003310711,0.00007650196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001579572,"about_ca_system_score_gemma":0.00008153855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003741017,"about_ca_topic_score_gemma":0.0001198801,"domain_scores_codex":[0.9986623,0.00001394122,0.0005288852,0.0003233911,0.0001717976,0.0002996845],"domain_scores_gemma":[0.9993805,0.0002042445,0.00002875289,0.0002171442,0.00008900637,0.00008040472],"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":[0.00002600985,0.00003713428,0.00004315819,0.0004391448,0.00009033323,0.000006623311,0.000533637,0.9797772,0.003510919,0.0007534369,0.00008327205,0.01469915],"study_design_scores_gemma":[0.0002049744,0.0000763998,0.00004595246,0.0002570231,0.0000857062,0.000002798557,0.0001177664,0.9709583,0.02709656,0.0001115163,0.000782844,0.0002601581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04980021,0.0002897189,0.9450568,0.00005693643,0.001188145,0.0006622611,0.0003236761,0.002514862,0.0001074072],"genre_scores_gemma":[0.9969578,0.00002819915,0.002009999,0.00002674092,0.00003791302,0.0005242379,0.00002617523,0.00008094565,0.0003080066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9471576,"threshold_uncertainty_score":0.9999863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03485154596502552,"score_gpt":0.2475198156653546,"score_spread":0.212668269700329,"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."}}