{"id":"W1528473409","doi":"","title":"Calibration of microscopic traffic model for simulating safety performance","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Traffic control and management","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Calibration; Computer science; Traffic simulation; Measure (data warehouse); Function (biology); Simulation; Data mining; Reliability engineering; Engineering; Statistics; Microsimulation; Mathematics; Transport 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003786938,0.0003608384,0.0005070822,0.0009527084,0.0006052933,0.00009593913,0.0005637912,0.000314466,0.0001036758],"category_scores_gemma":[0.0001832503,0.0003841332,0.0002202932,0.001177184,0.0004363977,0.0007283931,0.000008673491,0.001432694,0.00001160733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009410904,"about_ca_system_score_gemma":0.0002853269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003219459,"about_ca_topic_score_gemma":0.009102787,"domain_scores_codex":[0.9944974,0.0001649039,0.001319636,0.0006743899,0.001999457,0.001344184],"domain_scores_gemma":[0.9961608,0.0008646481,0.0001265257,0.0005107239,0.00195492,0.0003823551],"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":[0.000657721,0.0001470476,0.003156482,0.001564638,0.00008491199,0.000005162699,0.005462637,0.936965,0.03173101,0.002427198,0.00110573,0.01669247],"study_design_scores_gemma":[0.002361818,0.0003457323,0.05855817,0.0001692223,0.00004197573,1.199673e-7,0.001390198,0.9275107,0.004666115,0.0002326271,0.004302453,0.0004208067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.970748,0.00008772486,0.0245407,0.0003329239,0.0002970557,0.00249089,0.000582945,0.0004206632,0.0004990755],"genre_scores_gemma":[0.9903448,0.0001925787,0.007470259,0.00001853496,0.000160687,0.0005787365,0.0005073376,0.000116138,0.000610934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05540169,"threshold_uncertainty_score":0.9998611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03226653438919463,"score_gpt":0.3241136281340674,"score_spread":0.2918470937448727,"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."}}