{"id":"W2947057187","doi":"10.11159/cdsr19.132","title":"Short term predictions of preceding vehicle speeds for connected and automated vehicles","year":2019,"lang":"en","type":"article","venue":"Proceedings of the International Conference of Control, Dynamic systems, and Robotics","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Term (time); Computer science; Automotive engineering; Real-time computing; Engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004622514,0.0005774552,0.0002639916,0.0004680828,0.0002223703,0.0003244235,0.0004638461,0.0006800101,0.000481798],"category_scores_gemma":[0.001865905,0.0002745481,0.0002955536,0.0002493523,0.0002490734,0.0004265737,0.0002346767,0.0005292714,0.000138723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005524589,"about_ca_system_score_gemma":0.0003773119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03505632,"about_ca_topic_score_gemma":0.02819244,"domain_scores_codex":[0.9999031,0.000019652,0.000005595117,0.00003325404,0.00001720147,0.00002124057],"domain_scores_gemma":[0.9994235,0.0002957804,0.00006725205,0.00003840467,0.0001346136,0.00004051319],"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":[0.000229787,0.0001051512,0.01041136,0.00002372068,0.00002926192,0.0001057308,0.00004670908,0.9699406,0.002234109,0.000229712,0.000343859,0.01629993],"study_design_scores_gemma":[0.000001351226,0.0000151565,0.001622258,6.847314e-7,0.000001563782,0.000002471081,0.000006519664,0.9979741,0.0003011528,0.00005841156,0.00001448411,0.00000177068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900653,0.00007407738,0.00915895,0.00005703974,0.00001374736,0.000008582148,0.0001055997,0.000113201,0.000403584],"genre_scores_gemma":[0.9987577,0.00001651743,0.0008879403,0.000002882904,0.000002294625,0.000002344368,0.0001438326,0.000003509459,0.0001829539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03505632,"threshold_uncertainty_score":0.06970453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01255144179505887,"score_gpt":0.2269630962836909,"score_spread":0.214411654488632,"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."}}