{"id":"W2891392030","doi":"10.1080/24725854.2018.1519744","title":"Integrated design of emergency shelter and medical networks considering diurnal population shifts in urban areas","year":2018,"lang":"en","type":"article","venue":"IISE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Natural Science Foundation of China","keywords":"Solver; Population; Benders' decomposition; Decomposition; Scale (ratio); Integer programming; Computer science; Network planning and design; Operations research; Mathematical optimization; Simulation; Geography; Engineering; Mathematics; Algorithm; Telecommunications; Medicine; Environmental health; Cartography","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003432169,0.0001134123,0.0001384828,0.0002439974,0.0001177426,0.0000284138,0.00008600853,0.00006875442,0.004144849],"category_scores_gemma":[0.00004857783,0.0001096579,0.00003882022,0.0004684513,0.00005703043,0.0004735349,0.0000112422,0.0001246054,0.00003002661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001981557,"about_ca_system_score_gemma":0.00001250741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002765972,"about_ca_topic_score_gemma":0.005825038,"domain_scores_codex":[0.9990501,0.00002253059,0.0004005338,0.0001835273,0.0001757004,0.0001675465],"domain_scores_gemma":[0.9996957,0.00001451318,0.00004982044,0.0001207364,0.00009601891,0.00002316723],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00112522,0.002450884,0.4652558,0.001322095,0.000634722,0.00004692348,0.003547811,0.2238536,0.001095431,0.02782376,0.01485097,0.2579928],"study_design_scores_gemma":[0.0006170824,0.00002171212,0.1641478,0.0001278073,0.00007421576,9.579859e-7,0.0002849737,0.8297702,0.00002007986,0.001194642,0.003484451,0.0002560656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3038904,0.00006626473,0.6929861,0.0007318137,0.0009534156,0.0003026653,0.000001822986,0.00007990177,0.0009876167],"genre_scores_gemma":[0.9992228,0.00006714093,0.0002587556,0.0001552166,0.0001735105,0.00001774072,0.00001386493,0.00001023556,0.00008078573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6953323,"threshold_uncertainty_score":0.9967655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03645776037515437,"score_gpt":0.2530371039577263,"score_spread":0.2165793435825719,"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."}}