{"id":"W2904932247","doi":"10.1049/iet-its.2018.5351","title":"Hardware and software architecture of intelligent vehicles and road verification in typical traffic scenarios","year":2018,"lang":"en","type":"article","venue":"IET Intelligent Transport Systems","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; China Postdoctoral Science Foundation","keywords":"Software; Intelligent transportation system; Embedded system; Architecture; Robustness (evolution); Engineering; Computer science; Transport engineering; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0002241136,0.0002145376,0.0003613137,0.0001837248,0.00004380143,0.00001006025,0.0001536827,0.0002979708,0.00001845622],"category_scores_gemma":[0.00001159468,0.0002048641,0.00004757795,0.0001785351,0.0002679824,0.00005900376,0.00001155776,0.0002971958,0.00001247474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004655959,"about_ca_system_score_gemma":0.00001989361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005273003,"about_ca_topic_score_gemma":0.0003348334,"domain_scores_codex":[0.9987507,0.00002980588,0.0005520965,0.0002895974,0.0001255479,0.0002521894],"domain_scores_gemma":[0.9995292,0.00003755614,0.00005308198,0.0002541552,0.00004701695,0.00007902294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001084981,0.0004756923,0.1734112,0.005083021,0.0005374494,0.0001033114,0.03775945,0.1866725,0.007791074,0.003448603,0.0001763421,0.5834564],"study_design_scores_gemma":[0.002813332,0.002099471,0.6323833,0.003944637,0.0003701898,0.0005687085,0.008830576,0.2289615,0.06886422,0.001411216,0.04630551,0.003447321],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9606397,0.003378256,0.03486366,0.00004663557,0.0002519545,0.0004127323,0.00003288707,0.0003068435,0.00006730243],"genre_scores_gemma":[0.9987943,0.000670524,0.000359396,0.000008810876,0.00005240453,0.00003026984,0.00002170097,0.00003152734,0.0000310633],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5800091,"threshold_uncertainty_score":0.8354115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01130988079267965,"score_gpt":0.211970443329904,"score_spread":0.2006605625372244,"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."}}