{"id":"W4312888502","doi":"10.1109/access.2022.3220321","title":"Pedestrian Traffic Characterization Based on Pedestrian Response","year":2022,"lang":"en","type":"article","venue":"IEEE Access","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Pedestrian; Simulation; Computer science; Emergency response; Transport engineering; Engineering; Medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001882002,0.0003557898,0.0003402125,0.0007760216,0.0001954178,0.000293812,0.0002045139,0.0002563963,0.000706211],"category_scores_gemma":[0.0007299265,0.0001118722,0.0002386985,0.0004204483,0.0001585716,0.000266917,0.0002760066,0.0001473671,0.0002153254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002126524,"about_ca_system_score_gemma":0.0001935141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002165755,"about_ca_topic_score_gemma":0.00194278,"domain_scores_codex":[0.9998263,0.00004100567,0.000006746937,0.00004331925,0.00005339143,0.00002924493],"domain_scores_gemma":[0.9997277,0.00005091331,0.00006389402,0.00002418063,0.00009552047,0.00003781651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0009645848,0.0004934787,0.1347235,0.000190762,0.00009709868,0.001110548,0.0007008388,0.6726639,0.09994458,0.002183126,0.001774426,0.08515318],"study_design_scores_gemma":[0.000004195075,0.0002372115,0.03866573,0.000007912246,0.00001953217,0.0002241448,0.000288838,0.952405,0.007386165,0.0002866681,0.0004452316,0.0000294358],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9618922,0.00003411086,0.03606346,0.00002540155,0.00001690102,0.00003103301,0.0001399772,0.0001750838,0.001621814],"genre_scores_gemma":[0.9974791,0.00002041083,0.002031895,0.000003184443,0.000002456433,0.000009292982,0.0001183577,0.000005175817,0.0003301028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002165755,"threshold_uncertainty_score":0.004306257,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02108455368379627,"score_gpt":0.2617927291378744,"score_spread":0.2407081754540782,"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."}}