{"id":"W4403458078","doi":"10.1016/j.physa.2024.130174","title":"A following model considering multiple vehicles from the driver's front and rear perspectives","year":2024,"lang":"en","type":"article","venue":"Physica A Statistical Mechanics and its Applications","topic":"Traffic control and management","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Front (military); Computer science; Car model; Automotive engineering; Statistical physics; Physics; Meteorology; 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":[0.0005802684,0.001047809,0.001717571,0.0008024712,0.001102295,0.002733541,0.003238203,0.005411433,0.01029986],"category_scores_gemma":[0.001081877,0.0007496953,0.001403688,0.0009751066,0.001149869,0.002482718,0.001720818,0.002017082,0.001972708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00105512,"about_ca_system_score_gemma":0.001165765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01562274,"about_ca_topic_score_gemma":0.008902026,"domain_scores_codex":[0.9994623,0.0001112433,0.00001847536,0.0002068975,0.00009791367,0.0001031792],"domain_scores_gemma":[0.9993568,0.0002035626,0.0001251281,0.00004546992,0.000172252,0.00009683814],"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":[0.0001999234,0.0001392335,0.002154183,0.0002256382,0.0001323288,0.001437633,0.0003998325,0.7635657,0.005334233,0.2133703,0.004153917,0.008887028],"study_design_scores_gemma":[0.00004862952,0.00007600443,0.000557246,0.00002143564,0.00005260021,0.0002031418,0.00008919534,0.9742343,0.0003305236,0.02205512,0.002282168,0.00004970542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1115856,0.001957371,0.7948616,0.00590454,0.001078436,0.0002017439,0.001896065,0.0003884457,0.08212616],"genre_scores_gemma":[0.8521878,0.001583701,0.02374513,0.0006198286,0.000556342,0.0003103854,0.0007321833,0.00008741055,0.1201773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01562274,"threshold_uncertainty_score":0.03445649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01059683286481226,"score_gpt":0.2216831121727784,"score_spread":0.2110862793079661,"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."}}