{"id":"W2346697296","doi":"10.1002/atr.1381","title":"A comparison between PARAMICS and VISSIM in estimating automated field‐measured traffic conflicts at signalized intersections","year":2016,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"VisSim; Microsimulation; Calibration; Traffic simulation; Intersection (aeronautics); Field (mathematics); Engineering; Simulation; Transport engineering; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.00146608,0.0007036116,0.000499525,0.001068417,0.0002189367,0.0006650086,0.0007056671,0.0004710336,0.0009329809],"category_scores_gemma":[0.003810684,0.0003074618,0.0004217025,0.0006058672,0.0002329454,0.0005951211,0.0006428632,0.000423805,0.0001385159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007307327,"about_ca_system_score_gemma":0.001024827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01252758,"about_ca_topic_score_gemma":0.006600594,"domain_scores_codex":[0.9994261,0.0002666084,0.00002823579,0.00008690354,0.000133752,0.00005840234],"domain_scores_gemma":[0.9976904,0.001204993,0.000261928,0.0002858164,0.0004559805,0.0001009252],"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":[0.0001584224,0.00005148316,0.01196321,0.00002744922,0.00004605902,0.00002180628,0.00002919055,0.9725687,0.001089329,0.0004067006,0.0001562365,0.01348145],"study_design_scores_gemma":[0.000005610344,0.00005012988,0.001374129,0.000004305581,0.000005995611,0.000005592795,0.00002113319,0.9974684,0.0008798735,0.00007615081,0.0001033382,0.000005478676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9184362,0.0001508422,0.07645132,0.0001058033,0.00002682556,0.00004695021,0.000365329,0.001270343,0.003146292],"genre_scores_gemma":[0.9882691,0.00003164709,0.01121201,0.00001339362,0.000002993686,0.0000217283,0.0001852789,0.00002604863,0.0002378846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01252758,"threshold_uncertainty_score":0.02490932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01328296174834179,"score_gpt":0.2662859605208274,"score_spread":0.2530029987724856,"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."}}