{"id":"W3200994258","doi":"10.29173/mocs190","title":"Toward a Simulation-based Approach for Emergency Evacuation Route Planning in Metro Stations","year":2015,"lang":"en","type":"article","venue":"Modular and Offsite Construction (MOC) Summit Proceedings","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Emergency evacuation; Pedestrian; Computer science; Metro station; Transport engineering; Route planning; Operations research; Emergency rescue; Selection (genetic algorithm); Simulation; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000309467,0.0002021389,0.0002128834,0.0003748972,0.0001039217,0.00008948347,0.00007771192,0.0001342437,0.00001175053],"category_scores_gemma":[0.000144681,0.0002283692,0.00005969096,0.0004566076,0.00003661495,0.0005063,0.0000128314,0.0001407138,0.000002391162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162953,"about_ca_system_score_gemma":0.00004241612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001116962,"about_ca_topic_score_gemma":0.00001351337,"domain_scores_codex":[0.9988169,0.000009645597,0.000410288,0.0002873514,0.0002347362,0.0002410981],"domain_scores_gemma":[0.999316,0.00003642574,0.00008871274,0.00007583587,0.0003512756,0.0001317935],"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":[0.00004341735,0.00002374146,0.08212572,0.0001702627,0.00002988508,3.44801e-7,0.0008896238,0.9093784,0.0003672671,0.002033405,0.0001474236,0.004790474],"study_design_scores_gemma":[0.001185062,0.00003824456,0.003360193,0.00002286169,0.00003907277,0.000001048407,0.002403827,0.9904913,0.0002719542,0.001105281,0.0008252201,0.0002559022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4156229,0.0001802268,0.5826994,0.00004592077,0.0002039418,0.000388548,0.00002650154,0.0001806937,0.0006518152],"genre_scores_gemma":[0.9608697,0.00001242577,0.03860432,0.00002672823,0.0000853865,0.0001155962,0.0002039411,0.00003471084,0.00004718616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5452467,"threshold_uncertainty_score":0.9312625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04509735517089215,"score_gpt":0.2724912669953558,"score_spread":0.2273939118244636,"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."}}