{"id":"W2808994316","doi":"10.1287/trsc.2017.0810","title":"Performance Approximation of Emergency Service Systems with Priorities and Partial Backups","year":2018,"lang":"en","type":"article","venue":"Transportation Science","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Polytechnique Montréal","funders":"","keywords":"Queue; Queueing theory; Service (business); Computer science; Operations research; Downtown; Service system; Response time; Computer network; Engineering; Operating system; Business; Geography","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":[0.002026749,0.0007750538,0.000821027,0.0006005701,0.0004300956,0.001092211,0.001191531,0.000731685,0.001720659],"category_scores_gemma":[0.009028398,0.0003491041,0.0005386804,0.0006162593,0.0008208651,0.0007532767,0.0009922567,0.0009533355,0.0002117553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001925081,"about_ca_system_score_gemma":0.001404692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01651875,"about_ca_topic_score_gemma":0.004409385,"domain_scores_codex":[0.9992011,0.0002729344,0.00002916019,0.00008681043,0.0002023032,0.0002076683],"domain_scores_gemma":[0.996857,0.001887213,0.000335418,0.0002172316,0.0005715523,0.0001314755],"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":[0.00004046461,0.000008223541,0.0004318271,0.00001783701,0.000006986941,0.00002978297,0.00003556338,0.9905104,0.0004260209,0.006355776,0.0002123336,0.001924765],"study_design_scores_gemma":[0.000001272091,0.000005745186,0.00008154345,0.000002163797,0.000001285478,0.000004821837,0.000006782135,0.9988657,0.00005634808,0.0009203231,0.00005229433,0.000001629098],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2090764,0.0008444106,0.7793434,0.0007515438,0.0000749054,0.00006367181,0.0002945532,0.0004506112,0.009100517],"genre_scores_gemma":[0.9830892,0.0002602368,0.01452389,0.00003174599,0.00002442684,0.0000378187,0.0001223719,0.00003930689,0.001871029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01651875,"threshold_uncertainty_score":0.0328452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03182437626683948,"score_gpt":0.2410435268289963,"score_spread":0.2092191505621568,"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."}}