{"id":"W2903070283","doi":"","title":"Towards cognitive automotive environment modelling: reasoning based on vector representations.","year":2018,"lang":"en","type":"article","venue":"The European Symposium on Artificial Neural Networks","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Automotive industry; Cognition; Artificial intelligence; Cognitive science; Engineering; Psychology; Neuroscience","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":[0.0007624835,0.0009464064,0.0007148955,0.001067905,0.0005098445,0.002945593,0.002625716,0.001264607,0.003404613],"category_scores_gemma":[0.005311688,0.0006732743,0.002120288,0.001089141,0.001114507,0.005878109,0.002183882,0.001997813,0.0008184427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008981451,"about_ca_system_score_gemma":0.001022158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01689703,"about_ca_topic_score_gemma":0.01593384,"domain_scores_codex":[0.9994761,0.0001705286,0.00004754309,0.0001234834,0.000113905,0.00006838662],"domain_scores_gemma":[0.9989317,0.0005242109,0.0001036486,0.000170842,0.0001927946,0.00007688325],"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":[0.0002578395,0.0002255198,0.002794252,0.0004831899,0.0003638079,0.0005269353,0.001059953,0.5098462,0.003874623,0.2932703,0.009602044,0.1776954],"study_design_scores_gemma":[0.0000206674,0.00002275296,0.0002512043,0.00004973222,0.00004831253,0.00005410163,0.0001482694,0.7791989,0.0008759263,0.2164446,0.002868389,0.00001716336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01456788,0.0005014879,0.9784494,0.0004714223,0.00006036818,0.00005243593,0.0003681147,0.0007479188,0.004780985],"genre_scores_gemma":[0.5722665,0.00093218,0.4219466,0.0002504232,0.00006454624,0.0001582808,0.001308759,0.0001426276,0.002929962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01689703,"threshold_uncertainty_score":0.03359735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01739829038270649,"score_gpt":0.221874184957842,"score_spread":0.2044758945751355,"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."}}