{"id":"W2295859842","doi":"","title":"Calibration of Driving Behavior Models using Derivative-Free Optimization and Video Data for Montreal Highways","year":2016,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Traffic control and management","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"VisSim; Calibration; Software; Flexibility (engineering); Traffic simulation; Computer science; Field (mathematics); Simulation; Intelligent transportation system; Real-time computing; Microsimulation; Engineering; 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":[0.0009961829,0.0009167433,0.0003786903,0.001069875,0.0006013056,0.000592508,0.001188001,0.0008070482,0.001064336],"category_scores_gemma":[0.002507737,0.0003818319,0.0005914749,0.0009561144,0.0004543315,0.0003851692,0.0003388067,0.000693857,0.0001565423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00416192,"about_ca_system_score_gemma":0.002190017,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5581207,"about_ca_topic_score_gemma":0.4975891,"domain_scores_codex":[0.999708,0.00008900077,0.0000152102,0.00007122445,0.00006490065,0.0000515296],"domain_scores_gemma":[0.9991541,0.0003696667,0.00008679152,0.00007523144,0.0002698824,0.00004431715],"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":[0.00003258663,0.00005927445,0.004136757,0.00001612849,0.00001754689,0.00003896901,0.00002950267,0.9884095,0.0009234063,0.0003957966,0.0003779437,0.005562492],"study_design_scores_gemma":[0.000006255023,0.00001319695,0.00302138,0.000002255214,0.000004102738,0.000003423592,0.00001451494,0.9958919,0.000747583,0.00008546965,0.0001992079,0.0000106953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9120571,0.0001276036,0.07952629,0.0001955523,0.00003657384,0.000162477,0.002305304,0.00139993,0.004189181],"genre_scores_gemma":[0.9775205,0.00005424441,0.0196964,0.00001464492,0.000003537602,0.00005200614,0.001821449,0.00006695985,0.0007702069],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4418793,"threshold_uncertainty_score":0.8889633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02023102787357144,"score_gpt":0.2215138863357333,"score_spread":0.2012828584621618,"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."}}