{"id":"W109459921","doi":"10.1023/a:1026134121255","title":"A Probabilistic Minimax Location Problem on the Plane","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Solver; Theory of computation; Minimax; Computer science; Mathematical optimization; Regular polygon; Software; Applied mathematics; Function (biology); Mathematics; Algorithm; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003315385,0.0009350855,0.002822917,0.001212532,0.000807129,0.002985111,0.002265319,0.003818448,0.006354267],"category_scores_gemma":[0.01709738,0.001312195,0.001129808,0.002097672,0.002027057,0.004693496,0.002433554,0.003023606,0.0004213961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001830252,"about_ca_system_score_gemma":0.001321381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003080388,"about_ca_topic_score_gemma":0.001764959,"domain_scores_codex":[0.998491,0.0007888196,0.00006119833,0.0003078732,0.0002086389,0.0001424068],"domain_scores_gemma":[0.9892267,0.009083732,0.0007390348,0.0002595257,0.0003796849,0.0003112408],"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":[0.0002980682,0.00006714422,0.000676844,0.0001758484,0.00008389923,0.0001073443,0.00009784299,0.8171902,0.0003461557,0.1614124,0.005009449,0.01453485],"study_design_scores_gemma":[0.00008757559,0.00005936175,0.0002892821,0.00002890876,0.00002078998,0.00005013532,0.00003642938,0.8126972,0.0001202357,0.185329,0.001264625,0.00001651333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07841507,0.0016787,0.901502,0.005505231,0.0001514067,0.0001013701,0.0009083381,0.0002090537,0.01152888],"genre_scores_gemma":[0.8327456,0.002487552,0.1468091,0.0005610842,0.0005673934,0.0003893699,0.001289027,0.0002147071,0.01493622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006354267,"threshold_uncertainty_score":0.02125716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2890206876650567,"score_gpt":0.3925561140424441,"score_spread":0.1035354263773874,"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."}}