{"id":"W4317632833","doi":"10.2514/6.2023-2192","title":"Attack-tolerant Trajectory Prediction using Generative Adversarial Network Secured by Blockchain Application to the UAS-S4 Ehécatl","year":2023,"lang":"en","type":"article","venue":"AIAA SCITECH 2023 Forum","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Adversarial system; Computer science; Trajectory; Artificial neural network; Artificial intelligence; Data mining; Blockchain; Deep learning; Machine learning; Computer security","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":[0.0005462996,0.0004618402,0.0003544086,0.0002278627,0.000255403,0.0003556013,0.0005963836,0.0005113405,0.003055839],"category_scores_gemma":[0.001574553,0.0001529825,0.0003223022,0.0001686391,0.0004110481,0.0005072095,0.0008085411,0.0007463873,0.0003170901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006457969,"about_ca_system_score_gemma":0.0007379811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0101517,"about_ca_topic_score_gemma":0.008530587,"domain_scores_codex":[0.9998022,0.0000523869,0.000007870482,0.00003732305,0.0000581557,0.00004215407],"domain_scores_gemma":[0.9994135,0.0002966602,0.00005053851,0.0000922984,0.0001056277,0.00004132692],"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":[0.00005455836,0.00001266376,0.0008423448,0.00001466655,0.000006942141,0.00006606021,0.00001429485,0.989989,0.0008999263,0.001125521,0.0003699789,0.006603968],"study_design_scores_gemma":[0.00000266473,0.00001260306,0.00007869704,0.000001647238,9.497818e-7,0.000006630005,0.000002672686,0.9987682,0.0005236986,0.0004748658,0.0001259177,0.000001407163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3764417,0.0003817179,0.6032048,0.0008683208,0.0001454864,0.0002212759,0.0007932429,0.00433767,0.01360582],"genre_scores_gemma":[0.983308,0.00006060289,0.01436766,0.00003692806,0.000006281977,0.00004934207,0.0002503499,0.00004275058,0.001878064],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0101517,"threshold_uncertainty_score":0.02018517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00970730986334685,"score_gpt":0.2248795940103976,"score_spread":0.2151722841470507,"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."}}