{"id":"W2034577739","doi":"10.1007/s00170-013-5337-7","title":"A new hybrid approach to discrete multiple facility location problem","year":2013,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Facility location problem; Tabu search; Mathematical optimization; Set (abstract data type); Lagrangian relaxation; 1-center problem; Computer science; Location model; Scale (ratio); Relaxation (psychology); Mathematics; Operations research","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":[],"consensus_categories":[],"category_scores_codex":[0.0008123183,0.000879849,0.001348089,0.0009336932,0.0004802787,0.001498019,0.00278369,0.001526315,0.005502919],"category_scores_gemma":[0.001637746,0.0006089656,0.000974852,0.001475191,0.0005892495,0.001588067,0.001762697,0.001385981,0.0006482148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006856809,"about_ca_system_score_gemma":0.0007629642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002559802,"about_ca_topic_score_gemma":0.002655022,"domain_scores_codex":[0.9992562,0.0002526526,0.00003141439,0.0001546925,0.0002298936,0.00007514749],"domain_scores_gemma":[0.9991344,0.0005437384,0.00005145746,0.00007087591,0.0001364002,0.00006322523],"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":[0.0001120718,0.000134287,0.0004522614,0.0002417072,0.00009776177,0.0001533565,0.00006336932,0.869246,0.002932221,0.04835349,0.00374593,0.07446767],"study_design_scores_gemma":[0.00001329709,0.00002374784,0.00003764465,0.000004101833,0.000007337729,0.00002300265,0.000008033833,0.9920345,0.0001445422,0.006504214,0.001194675,0.00000484168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005485282,0.0002369023,0.9905461,0.0001552065,0.0001228835,0.00003352883,0.00005638704,0.0001026873,0.003261022],"genre_scores_gemma":[0.310801,0.0005286274,0.6743106,0.0002585652,0.0003633033,0.0002826208,0.0003616544,0.0001460427,0.01294764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005502919,"threshold_uncertainty_score":0.01840907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219753406767517,"score_gpt":0.2235922443426674,"score_spread":0.2113947102749923,"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."}}