{"id":"W2999305622","doi":"10.1155/2020/2797420","title":"An Improved Car-Following Speed Model considering Speed of the Lead Vehicle, Vehicle Spacing, and Driver’s Sensitivity to Them","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Sensitivity (control systems); Acceleration; Benchmark (surveying); Simulation; Automotive engineering; Engineering; Calibration; Statistics; Mathematics","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":[0.0005599409,0.0006086302,0.000623714,0.0005447058,0.000312025,0.0007077536,0.001709588,0.001032127,0.001450589],"category_scores_gemma":[0.001251238,0.0003744874,0.0008314993,0.00048024,0.0003449106,0.001030863,0.0005944467,0.0007477066,0.0002643812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008108222,"about_ca_system_score_gemma":0.001295932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02700061,"about_ca_topic_score_gemma":0.01347149,"domain_scores_codex":[0.9996645,0.000051223,0.0000180298,0.0001233997,0.00008518993,0.00005764723],"domain_scores_gemma":[0.9996338,0.0001155906,0.00005797327,0.00002765377,0.0001410524,0.00002390209],"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":[0.00001564161,0.0000135253,0.001160599,0.00001334172,0.00001318571,0.00002610484,0.0000205775,0.9929287,0.0006384925,0.001202634,0.0001705359,0.003796711],"study_design_scores_gemma":[0.000002461218,0.000009902887,0.0003095095,0.000001489488,0.000006747214,0.000006600438,0.000003205377,0.9990276,0.0001342161,0.0003056549,0.000189604,0.000003071018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.281106,0.0006399465,0.7045488,0.000471921,0.0001473554,0.0001088782,0.0008729057,0.0007477019,0.01135652],"genre_scores_gemma":[0.9856896,0.0001475872,0.01047686,0.00003272705,0.00002003155,0.00005843069,0.0003179084,0.00003130906,0.003225568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02700061,"threshold_uncertainty_score":0.05368692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123632466676497,"score_gpt":0.2146247876877087,"score_spread":0.202261541020059,"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."}}