{"id":"W4413380156","doi":"10.3390/math13162616","title":"Traffic Characterization Based on Driver Reaction","year":2025,"lang":"en","type":"article","venue":"Mathematics","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Characterization (materials science); Computer science; Materials science; Nanotechnology","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":[0.0001357941,0.0003722126,0.0002868645,0.0003400048,0.0001940775,0.0005212498,0.0005607228,0.0003398309,0.001205191],"category_scores_gemma":[0.0003652786,0.00009629688,0.0003218106,0.000324306,0.0002324797,0.0005140662,0.000389266,0.0003347934,0.000212862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000378856,"about_ca_system_score_gemma":0.000372523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003724648,"about_ca_topic_score_gemma":0.002236328,"domain_scores_codex":[0.9998572,0.00002249913,0.000004971414,0.00004033013,0.00004326077,0.00003163136],"domain_scores_gemma":[0.9998642,0.00002635541,0.00003157743,0.00002007124,0.00004020491,0.0000175938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00007136918,0.0000942909,0.007127576,0.00002333419,0.00001784886,0.0001129158,0.00007730541,0.9579571,0.01648927,0.008340343,0.0005601262,0.009128562],"study_design_scores_gemma":[0.000001693808,0.00002065137,0.001007487,6.75867e-7,0.000002556255,0.00001436689,0.0000153645,0.9970739,0.001123439,0.0004403808,0.0002928853,0.000006586469],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5565975,0.00007968274,0.4328952,0.00008271815,0.00005513649,0.00009861687,0.0004075788,0.000399614,0.009383883],"genre_scores_gemma":[0.9917282,0.00005196786,0.006054359,0.000009269314,0.000006752398,0.00003026844,0.0002041353,0.00001563274,0.001899543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003724648,"threshold_uncertainty_score":0.007405937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005492989736581258,"score_gpt":0.1873555362716124,"score_spread":0.1818625465350311,"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."}}