{"id":"W4285519094","doi":"10.2139/ssrn.3930617","title":"Online Facility Location","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Facility location problem; Regret; Computer science; Leverage (statistics); Facility management; Profit (economics); Operations research; Mathematical optimization; Engineering; Artificial intelligence; Mathematics; Machine learning","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003023475,0.0005921143,0.0003631036,0.00254749,0.0008520567,0.002851092,0.0009346606,0.00096645,0.588451],"category_scores_gemma":[0.002307036,0.000250648,0.0003181023,0.003340638,0.000171538,0.002616215,0.001657577,0.0006324774,0.4472892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004901362,"about_ca_system_score_gemma":0.0006637925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002408361,"about_ca_topic_score_gemma":0.004246778,"domain_scores_codex":[0.9996344,0.00005123591,0.00002325859,0.00005323172,0.0001785588,0.00005934283],"domain_scores_gemma":[0.9982795,0.0002332619,0.0001577116,0.0005279343,0.0004722749,0.0003293962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008924218,0.00008939474,0.001582431,0.0001264329,0.000004834994,0.0001260164,0.0001023216,0.0003495269,0.0008315789,0.005782243,0.7387249,0.2521911],"study_design_scores_gemma":[0.00001068999,0.00002228333,0.001640866,0.00005559059,0.000004682043,0.0001311409,0.0001124213,0.0004463391,0.0005678731,0.001284162,0.9957103,0.00001363897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005102591,0.0004040393,0.009570753,0.0008918792,0.0007567562,0.0001293181,0.02596126,0.008558751,0.9486246],"genre_scores_gemma":[0.0481298,0.0009518929,0.01011734,0.0006478241,0.0006211041,0.000145173,0.03325114,0.001784295,0.9043514],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.588451,"threshold_uncertainty_score":0.5870247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01767587141447088,"score_gpt":0.2347428420535306,"score_spread":0.2170669706390597,"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."}}