{"id":"W2223905903","doi":"","title":"Robust Facility Location under Demand Location Uncertainty","year":2013,"lang":"en","type":"preprint","venue":"TSpace","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Discretization; Facility location problem; Computer science; Mathematical optimization; A priori and a posteriori; Event (particle physics); Set (abstract data type); Robust optimization; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002168308,0.0009794203,0.001298876,0.0004951221,0.0003033408,0.001602803,0.001556228,0.001423597,0.002297796],"category_scores_gemma":[0.007226918,0.0006886927,0.001108383,0.0009404862,0.0009948455,0.001978038,0.001420241,0.001638433,0.0002280922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00179092,"about_ca_system_score_gemma":0.001077228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005919122,"about_ca_topic_score_gemma":0.002511345,"domain_scores_codex":[0.9982995,0.0007806484,0.00005803248,0.0003844513,0.0002541158,0.0002232206],"domain_scores_gemma":[0.9959921,0.00262368,0.0005934269,0.0003833742,0.0003133204,0.00009406178],"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":[0.00002107143,0.000006892362,0.0001083169,0.00001567814,0.00001192877,0.00002168709,0.0000111776,0.9891634,0.0002175888,0.00778549,0.0001520537,0.002484709],"study_design_scores_gemma":[0.000004991093,0.00001394162,0.00004772585,0.000002313757,0.000003182523,0.000007586949,0.000006199431,0.9938589,0.0001600174,0.005743407,0.0001479765,0.000003773602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02110852,0.0001625422,0.9770131,0.0002186039,0.00001802302,0.00002326705,0.0001221239,0.0001337153,0.00120014],"genre_scores_gemma":[0.9088483,0.0002775286,0.08831996,0.0000798289,0.00004453587,0.00008456544,0.0002212773,0.00006160656,0.002062287],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005919122,"threshold_uncertainty_score":0.01299411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07055034781393353,"score_gpt":0.2836288116806191,"score_spread":0.2130784638666856,"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."}}