{"id":"W2505685665","doi":"","title":"Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms","year":2010,"lang":"en","type":"article","venue":"","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Facility location problem; Metric (unit); Computer science; Mathematical optimization; Approximation algorithm; Probabilistic logic; Graphical model; Product (mathematics); Variety (cybernetics); Algorithm; Linear programming; Construct (python library); Inference; Metric space; Theoretical computer science; Mathematics; Artificial intelligence; Discrete mathematics","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":[0.001119767,0.0002030206,0.0001402021,0.0001437564,0.0006831831,0.0004963209,0.0003334882,0.00007241442,0.001694453],"category_scores_gemma":[0.0001579577,0.0001458096,0.00006932067,0.0008236514,0.0001240237,0.00130113,0.0001733744,0.0002748027,0.0005037898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003635118,"about_ca_system_score_gemma":0.00003063495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004536369,"about_ca_topic_score_gemma":0.001878347,"domain_scores_codex":[0.9985222,0.00001881555,0.0003989231,0.0003570709,0.0003580373,0.0003449057],"domain_scores_gemma":[0.9990224,0.00002135591,0.0001004311,0.0004720005,0.0003676521,0.00001616273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001051775,0.001237233,0.03505679,0.002522171,0.0004455583,0.00001310373,0.002193413,0.0557587,0.07131493,0.3585679,0.03010643,0.4426786],"study_design_scores_gemma":[0.000411843,0.000004295895,0.008211235,0.00002929608,0.00008607375,0.000001589664,0.001551991,0.8925563,0.0003205234,0.00443581,0.09189733,0.0004937388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6374364,0.00005810094,0.24742,0.01077127,0.003283592,0.001825022,0.000007429601,0.001112457,0.09808579],"genre_scores_gemma":[0.9949094,0.000001957392,0.002609523,0.001232574,0.0002833769,0.00002767369,0.00004242056,0.00001355032,0.0008795154],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8367976,"threshold_uncertainty_score":0.9992181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03453288988296742,"score_gpt":0.2430286853227779,"score_spread":0.2084957954398104,"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."}}