{"id":"W2474392009","doi":"10.1155/2017/3080859","title":"A Framework for Estimating Long Term Driver Behavior","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Electrical, Communications and Cyber Systems; National Science Foundation","keywords":"Term (time); Trajectory; State (computer science); Markov chain; Hidden Markov model; Advanced driver assistance systems; Estimation; Hybrid system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001123813,0.0006941732,0.0005369395,0.0009497938,0.0004746174,0.0009179439,0.001734999,0.0007726391,0.001769632],"category_scores_gemma":[0.002516553,0.0004401684,0.001028911,0.0006462134,0.0005287378,0.001141316,0.001079474,0.001099912,0.0006456628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006677302,"about_ca_system_score_gemma":0.001412606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01672029,"about_ca_topic_score_gemma":0.01293537,"domain_scores_codex":[0.99937,0.0001695156,0.00003646979,0.0001877836,0.0001800903,0.00005606031],"domain_scores_gemma":[0.9992639,0.0002539232,0.00009439408,0.0001095473,0.0002357804,0.00004252906],"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":[0.00007085603,0.000114795,0.006612374,0.0001188292,0.00017836,0.0002160617,0.0002714178,0.7298467,0.006377122,0.09902076,0.002549319,0.1546234],"study_design_scores_gemma":[0.000003192931,0.00004362487,0.001081017,0.00001304414,0.00001844553,0.00005646457,0.00002447605,0.9778692,0.0006228828,0.01767616,0.002565543,0.00002588581],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002286741,0.0001083878,0.9968443,0.00004512538,0.00001501139,0.00001401224,0.00008957281,0.0001474426,0.0004493544],"genre_scores_gemma":[0.3386115,0.0006821271,0.6545277,0.00009008143,0.000120898,0.0002435607,0.001002206,0.0001015832,0.004620264],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01672029,"threshold_uncertainty_score":0.03324592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246985880960833,"score_gpt":0.2858113911190858,"score_spread":0.2733415323094774,"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."}}