{"id":"W3080427371","doi":"10.1007/s11432-019-2844-3","title":"Investigating the dynamic memory effect of human drivers via ON-LSTM","year":2020,"lang":"en","type":"article","venue":"Science China Information Sciences","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Trajectory; Computer science; Economic shortage; Long short term memory; Sequence (biology); Range (aeronautics); Artificial intelligence; Estimation; Machine learning; Artificial neural network; Recurrent neural network; Engineering","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":[0.0001389093,0.0002596635,0.0001617144,0.0001414859,0.00009066016,0.0002743558,0.0002592376,0.0003053862,0.001738349],"category_scores_gemma":[0.001288505,0.00007811363,0.0001161878,0.0001338265,0.0001154175,0.0005657373,0.0002783617,0.0002833061,0.0002092243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001255207,"about_ca_system_score_gemma":0.0002156457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002296683,"about_ca_topic_score_gemma":0.002667791,"domain_scores_codex":[0.9999473,0.000008667477,0.000001887812,0.00001661565,0.000008635201,0.00001693031],"domain_scores_gemma":[0.9998123,0.0001001972,0.00001890958,0.00001670079,0.00003553355,0.00001639024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004511595,0.0008334639,0.0549947,0.0005509459,0.0003199465,0.0008148233,0.001095925,0.03858771,0.433267,0.00268407,0.004493308,0.4578465],"study_design_scores_gemma":[0.0001053557,0.001906318,0.1621345,0.00005457093,0.0004762983,0.000683926,0.001136595,0.7101832,0.1131676,0.006477752,0.003606074,0.00006779755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914573,0.0001281165,0.006326473,0.00009342826,0.00005544761,0.000008220522,0.00009412529,0.00006290592,0.001774097],"genre_scores_gemma":[0.9985323,0.00005057993,0.000823681,0.00003367166,0.000009607244,0.000003071963,0.00005126183,0.000006720736,0.0004891613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002296683,"threshold_uncertainty_score":0.005815327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007419482379214578,"score_gpt":0.2381106042542495,"score_spread":0.2306911218750349,"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."}}