{"id":"W3127315230","doi":"10.3390/su13031404","title":"Driver Behavior Classification at Stop-Controlled Intersections Using Video-Based Trajectory Data","year":2021,"lang":"en","type":"article","venue":"Sustainability","topic":"Traffic and Road Safety","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; Unavailability; Computer science; Intersection (aeronautics); Trajectory; DBSCAN; Data mining; Artificial intelligence; Machine learning; Engineering; Fuzzy clustering; Transport engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003663831,0.0003495096,0.000190302,0.00271255,0.000243564,0.0005364916,0.0003650561,0.0003198579,0.0004779718],"category_scores_gemma":[0.001640093,0.00008152811,0.0001921544,0.001601028,0.000139435,0.0004039268,0.0002574194,0.0002366384,0.0002215395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007515731,"about_ca_system_score_gemma":0.00073349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05565477,"about_ca_topic_score_gemma":0.08086237,"domain_scores_codex":[0.999718,0.00004927055,0.00001709179,0.00006578199,0.0001055949,0.00004428097],"domain_scores_gemma":[0.9990933,0.0001721911,0.0001758987,0.00005435872,0.0004389594,0.00006519881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006996053,0.0005991504,0.7115166,0.0001958491,0.0001795599,0.0005387113,0.001751542,0.0563325,0.03013227,0.001411535,0.002141547,0.1945012],"study_design_scores_gemma":[0.00002010552,0.0004461398,0.605324,0.00003945347,0.00007660298,0.0001881252,0.003157575,0.3740535,0.01358516,0.0006602686,0.002384217,0.00006483559],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.976431,0.00005794326,0.02030119,0.0000328616,0.000006838824,0.00009126063,0.001428601,0.0002446786,0.001405698],"genre_scores_gemma":[0.9848843,0.00007785771,0.01162254,0.000005558922,0.000002865685,0.00003375403,0.00279998,0.0000100706,0.0005630318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05565477,"threshold_uncertainty_score":0.1106616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03528578298085131,"score_gpt":0.2848782260553971,"score_spread":0.2495924430745458,"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."}}