{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003911853,0.0001019401,0.000111923,0.00001450639,0.0001177384,0.00009935551,0.00005480455,0.00001962048,0.000004853004],"category_scores_gemma":[0.00001810108,0.00007961882,0.00002628803,0.00004323906,0.00001259558,0.00005740561,0.00005075029,0.0001005904,0.00001084306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001670275,"about_ca_system_score_gemma":0.000007509353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001970053,"about_ca_topic_score_gemma":0.00002751103,"domain_scores_codex":[0.9994812,0.000007438373,0.00009495299,0.0002147385,0.00007874279,0.0001229481],"domain_scores_gemma":[0.9994299,0.0003861494,0.000006936956,0.0001083013,0.00001183327,0.00005685988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001869182,0.00001740147,7.136057e-7,0.0000295695,0.0001206479,0.000001743622,0.001212046,0.00297108,0.005486659,0.96421,0.0005336189,0.02541471],"study_design_scores_gemma":[0.0001131209,0.000007107717,0.00009268214,0.00001965148,0.00008240229,3.205773e-7,0.0004586845,0.9163593,0.00003059678,0.07877938,0.003962973,0.0000937816],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01108508,0.003777079,0.9832411,0.0007139511,0.00003864367,0.0003936099,0.0003254456,0.0002469178,0.0001781137],"genre_scores_gemma":[0.9933538,0.0004506008,0.005837349,0.00003007936,0.00005817882,0.0002275564,0.00001137486,0.00001884313,0.00001215571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9822688,"threshold_uncertainty_score":0.3246761,"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."}}