{"id":"W2789183464","doi":"10.1145/3102302","title":"Simulating Urban Pedestrian Crowds of Different Cultures","year":2018,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Israel Science Foundation","keywords":"Crowds; Pedestrian; Computer science; Crowd simulation; Crowd psychology; Macro; Dynamics (music); Artificial intelligence; Data science; Human–computer interaction; Computer security; Transport engineering; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004015354,0.0005426586,0.0003921696,0.0004468562,0.00072554,0.0008074712,0.0007976532,0.0008658923,0.001165969],"category_scores_gemma":[0.001619742,0.0003215941,0.0004818318,0.0005133127,0.0008046432,0.000750132,0.001233974,0.0004683457,0.000142252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120776,"about_ca_system_score_gemma":0.0006737037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03139998,"about_ca_topic_score_gemma":0.02088689,"domain_scores_codex":[0.9997982,0.00009112402,0.00000892797,0.00002975729,0.00003101645,0.00004098263],"domain_scores_gemma":[0.999361,0.0003049223,0.00008658171,0.0000629472,0.0000936643,0.00009087533],"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":[0.00005568905,0.00006291407,0.004601595,0.00002507068,0.00002618795,0.0001676661,0.0003120132,0.9872699,0.0008880468,0.00468134,0.0002660919,0.00164358],"study_design_scores_gemma":[0.00001734632,0.00003360059,0.0008415062,0.000006261575,0.000008033262,0.00001982879,0.0002354313,0.9963032,0.0004859936,0.001627325,0.0004111618,0.000010202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9642929,0.00008546493,0.02791742,0.0002158563,0.00002967171,0.00007501695,0.0002541261,0.0001043769,0.007025134],"genre_scores_gemma":[0.9921887,0.00007360475,0.006486408,0.00003079002,0.000005541878,0.00005111266,0.00009080259,0.000009659393,0.001063382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03139998,"threshold_uncertainty_score":0.06243438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0144078000942277,"score_gpt":0.2575260896450763,"score_spread":0.2431182895508486,"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."}}