{"id":"W2563293374","doi":"10.1007/s11047-016-9605-y","title":"On an integrated approach to resilient transportation systems in emergency situations","year":2017,"lang":"en","type":"article","venue":"Natural Computing","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"National Natural Science Foundation of China","keywords":"Computer science; Resilience (materials science); Generality; Variable (mathematics); Service (business); Mathematical optimization; Function (biology); Particle swarm optimization; Theory of computation; Flow network; Operations research; Engineering; Mathematics; Algorithm; Business","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":[0.0008744331,0.0007404439,0.0007066372,0.0008793909,0.001078912,0.002660665,0.001766758,0.0009411891,0.008383461],"category_scores_gemma":[0.002222934,0.0004149363,0.001194001,0.0008085273,0.0009878837,0.004248987,0.003991289,0.001750738,0.0008967223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008205519,"about_ca_system_score_gemma":0.001221585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004183515,"about_ca_topic_score_gemma":0.006021692,"domain_scores_codex":[0.9991785,0.0001930394,0.00005742834,0.0001789091,0.0002754361,0.0001167552],"domain_scores_gemma":[0.9994352,0.0001632798,0.00003242772,0.0001470069,0.0001455861,0.00007647501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000246416,0.0003946026,0.002062183,0.0002982888,0.0002333795,0.0004343059,0.0008296106,0.3515979,0.01103842,0.4470456,0.007559326,0.1782598],"study_design_scores_gemma":[0.00001963487,0.0001119327,0.0004181435,0.00006553752,0.0000836701,0.00008352635,0.000292063,0.858857,0.002163513,0.1206021,0.017282,0.00002098578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01155748,0.0002876362,0.9741711,0.0007022136,0.0001454087,0.0001006547,0.00006805584,0.0004065818,0.0125609],"genre_scores_gemma":[0.4303825,0.0009793241,0.553848,0.0003914635,0.0001890627,0.0002577984,0.0003306277,0.0002471923,0.01337398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008383461,"threshold_uncertainty_score":0.02804542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631111053294668,"score_gpt":0.2745996637157482,"score_spread":0.2582885531828015,"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."}}