{"id":"W7125926945","doi":"10.1109/ase63991.2025.00143","title":"ADPerf: Investigating and Testing Performance in Autonomous Driving Systems","year":2025,"lang":"","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Concordia University","funders":"","keywords":"Obstacle; Latency (audio); Bottleneck; Reliability (semiconductor); Obstacle avoidance; Point cloud; Autonomous system (mathematics); Lidar","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007916047,0.0004349712,0.0005886889,0.000534349,0.0003620624,0.0001221968,0.0003105796,0.0005759507,0.00001617897],"category_scores_gemma":[0.0003909666,0.0004964659,0.00003499145,0.001163126,0.0002779124,0.0003766046,0.0003338418,0.00114216,0.00002388363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003590349,"about_ca_system_score_gemma":0.0002184354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002357511,"about_ca_topic_score_gemma":0.00008307898,"domain_scores_codex":[0.997476,0.00006421458,0.0009914908,0.0005713687,0.0001068527,0.0007900241],"domain_scores_gemma":[0.9988648,0.0004496181,0.0001093081,0.0004173578,0.00005355968,0.0001053307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002660646,0.00002582451,0.8008143,0.00120731,0.00006260334,0.00001487982,0.0005063384,0.09261439,0.001992026,0.01509816,0.0000200817,0.08764144],"study_design_scores_gemma":[0.000411032,0.00004288866,0.2266135,0.001630439,0.00002527101,0.00002652409,0.0004959917,0.7687962,0.001041818,0.0001886432,0.0003613999,0.0003662904],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9375104,0.003924823,0.002007077,0.0002655248,0.0005787782,0.0004547235,0.000001467159,0.0008987307,0.05435848],"genre_scores_gemma":[0.9945861,0.0002255435,0.003882965,0.00006674109,0.00004591849,0.00005176802,0.000001227347,0.00004023237,0.00109957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6761818,"threshold_uncertainty_score":0.9997487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146334322622778,"score_gpt":0.2085514612079919,"score_spread":0.1970881179817641,"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."}}