{"id":"W2902266504","doi":"10.1080/03081060.2018.1541279","title":"Validation of an agent-based microscopic pedestrian simulation model in a crowded pedestrian walking environment","year":2018,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McMaster University","funders":"","keywords":"Pedestrian; Computer science; Simulation; Downtown; Calibration; Artificial intelligence; Transport engineering; Engineering; Statistics; Mathematics; Geography","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":[0.0004035899,0.0004516398,0.0005612088,0.0003832708,0.0004226372,0.0005834859,0.0007401066,0.0007016406,0.0007694656],"category_scores_gemma":[0.001109601,0.0002508656,0.0003759151,0.0002927065,0.0003823262,0.0003486342,0.0005325238,0.0003854859,0.0001456973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006273384,"about_ca_system_score_gemma":0.0012201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03241079,"about_ca_topic_score_gemma":0.01337121,"domain_scores_codex":[0.9998145,0.00005995565,0.00001001056,0.00002893363,0.00005718385,0.00002945355],"domain_scores_gemma":[0.9995316,0.0001944048,0.0000524489,0.0000585338,0.0001151808,0.0000478641],"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":[0.00001812308,0.00002527475,0.001011279,0.000008097564,0.000007214036,0.00004379694,0.00002106179,0.996515,0.0008172687,0.0003284971,0.00004212545,0.001162175],"study_design_scores_gemma":[0.000004013407,0.00001713582,0.0002187982,0.00000123885,0.000002294149,0.000005313033,0.000008733076,0.9992859,0.0003102057,0.00006038824,0.00008378315,0.000002347246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.867038,0.00007848594,0.1265555,0.0001527819,0.00004754257,0.00009893339,0.0002158863,0.0004492223,0.005363633],"genre_scores_gemma":[0.9879048,0.00004184376,0.01121979,0.00001214526,0.000002641,0.00004176155,0.00009196646,0.00001173705,0.000673293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03241079,"threshold_uncertainty_score":0.0644443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01541875205711673,"score_gpt":0.2596092468974919,"score_spread":0.2441904948403751,"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."}}