{"id":"W4319603022","doi":"10.31219/osf.io/rjue6","title":"Capacity Analysis of a Passenger Rail Hub using Integrated Railway and Pedestrian Simulation","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Arup Group (Canada); University of Toronto","funders":"","keywords":"Pedestrian; Transport engineering; Computer science; Nexus (standard); Simulation; Kinematics; Linkage (software); Dwell time; Urban rail transit; Engineering; Embedded system","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":[0.0004282466,0.000685218,0.0006146368,0.0008619546,0.0003827442,0.000775623,0.0006542862,0.0006570588,0.001946378],"category_scores_gemma":[0.001022758,0.0003585739,0.0007565392,0.0006154962,0.0004322401,0.0005019461,0.0008180836,0.0003479331,0.0001425028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001258431,"about_ca_system_score_gemma":0.001389736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05709362,"about_ca_topic_score_gemma":0.02211368,"domain_scores_codex":[0.9997947,0.00006178652,0.000007972664,0.00003507993,0.0000403824,0.00006010704],"domain_scores_gemma":[0.9995843,0.0001933323,0.00005948933,0.00003245121,0.00008263262,0.00004794739],"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":[0.00003265143,0.00001929549,0.001582723,0.000007792747,0.000007167303,0.00003559455,0.00002312923,0.9967253,0.0004131389,0.0002884458,0.00003291775,0.0008317481],"study_design_scores_gemma":[0.000003933232,0.00003385909,0.0006822403,0.000002271717,0.000006000987,0.000005250462,0.00002822334,0.9988236,0.0002445668,0.00008745305,0.00007875081,0.000003760088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9470393,0.00007742678,0.04543,0.0000639646,0.00001424303,0.00006648551,0.0003166231,0.0002826706,0.006709249],"genre_scores_gemma":[0.9969495,0.000030519,0.002286344,0.000004198294,0.000001671505,0.00001950827,0.00008505706,0.000009773715,0.0006133951],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05709362,"threshold_uncertainty_score":0.1135226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08845732936691138,"score_gpt":0.3013377435122431,"score_spread":0.2128804141453318,"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."}}