{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048382,0.0002884921,0.0001882283,0.00007833444,0.0004715448,0.00005424508,0.0003240617,0.00009470961,0.00007312637],"category_scores_gemma":[0.00002610872,0.0002327023,0.0001006164,0.000193576,0.0003504847,0.00006513442,0.00007019824,0.0006228928,0.0005323837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007296971,"about_ca_system_score_gemma":0.000008405331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005403776,"about_ca_topic_score_gemma":0.000002215183,"domain_scores_codex":[0.9982184,0.0004101325,0.0003288829,0.0003998214,0.000208106,0.0004346474],"domain_scores_gemma":[0.9991127,0.0001975923,0.00007877831,0.0004840927,0.00004070238,0.0000860951],"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":[0.0001637217,0.00005392622,0.00002279178,0.000001945746,0.00003018822,0.00002674759,0.0003234837,0.9828181,0.0002714516,0.0009329161,0.0003090362,0.01504569],"study_design_scores_gemma":[0.0002066204,0.000317569,0.001133428,0.00004259065,0.00003590221,0.000003644384,0.0000631595,0.9935078,0.003982384,0.0001130226,0.0003462412,0.0002476577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3314282,0.00008725627,0.4496014,0.003881972,0.001905686,0.00119864,0.00004156095,0.003036401,0.2088189],"genre_scores_gemma":[0.9979917,0.00002160635,0.0001441647,0.0006985752,0.0009134096,0.00001686088,0.00002231136,0.00009198388,0.00009941027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6665635,"threshold_uncertainty_score":0.9489324,"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."}}