{"id":"W2944746600","doi":"10.3389/fnbot.2019.00012","title":"Neural Network Based Uncertainty Prediction for Autonomous Vehicle Application","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neurorobotics","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Higher Education Discipline Innovation Project; National Natural Science Foundation of China","keywords":"Odometry; Computer science; Trajectory; Artificial neural network; Generalization; Artificial intelligence; Sensor fusion; Visual odometry; Orientation (vector space); Machine learning; Mobile robot; Robot; Mathematics","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":[0.0007249691,0.0005252841,0.000588279,0.000453922,0.000314346,0.0007435331,0.000667118,0.0007135971,0.001055102],"category_scores_gemma":[0.002239384,0.0002311086,0.0003284377,0.0005223771,0.0004563085,0.001014597,0.0007974314,0.0009215767,0.0002025189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007312245,"about_ca_system_score_gemma":0.0005762727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006082802,"about_ca_topic_score_gemma":0.003261687,"domain_scores_codex":[0.9997104,0.00007099466,0.00002010865,0.00006913071,0.0001007162,0.00002857119],"domain_scores_gemma":[0.9994051,0.0003159273,0.00007272511,0.00003289389,0.0001565859,0.00001684397],"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":[0.00003515485,0.0000122643,0.0003148504,0.00003809528,0.00001801127,0.00003894354,0.00002480031,0.9557739,0.001038412,0.007677625,0.0003848493,0.0346431],"study_design_scores_gemma":[7.596272e-7,0.000005062446,0.00005782677,0.000003376911,0.000002144836,0.000003815519,0.000002505246,0.9965792,0.0002393491,0.002918367,0.0001853742,0.000002203316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01157164,0.0006381237,0.9858434,0.0001911267,0.00003266545,0.00001606306,0.00005361225,0.0001730247,0.001480455],"genre_scores_gemma":[0.9259189,0.0009423759,0.07051487,0.00007293838,0.00009623222,0.0001020325,0.0001627998,0.00004253216,0.002147307],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006082802,"threshold_uncertainty_score":0.0120948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009047008414705978,"score_gpt":0.2140440513540685,"score_spread":0.2049970429393625,"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."}}