{"id":"W107574902","doi":"10.1023/a:1026190322164","title":"Location Among Regions with Varying Norms","year":2003,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Computer science; Facility location problem; Mathematical optimization; Variation (astronomy); Plane (geometry); Boundary (topology); Line (geometry); Mathematics; Algorithm; Geometry; Physics","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":[0.002635171,0.0001177453,0.0003902752,0.001676395,0.0007505414,0.002203306,0.000619997,0.0003700113,0.00524034],"category_scores_gemma":[0.02506551,0.000206967,0.0002749206,0.002590833,0.001143915,0.001486284,0.001409213,0.0004069246,0.000592726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001555459,"about_ca_system_score_gemma":0.0008067114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03497934,"about_ca_topic_score_gemma":0.05993289,"domain_scores_codex":[0.9957588,0.001949039,0.0002980945,0.0008139629,0.0006235772,0.0005565629],"domain_scores_gemma":[0.9760219,0.01011595,0.00501673,0.001866505,0.00614285,0.0008360199],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006003896,0.0000888861,0.9627522,0.00004903628,0.0001974399,0.0001955456,0.008813767,0.001711549,0.001176578,0.007695341,0.00112811,0.01559125],"study_design_scores_gemma":[0.00004160067,0.0001526304,0.9654376,0.00002598875,0.0001194473,0.0001839733,0.02316649,0.003096045,0.0007544344,0.003239456,0.003723605,0.00005865578],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939195,0.00008400586,0.0009096997,0.0001594735,0.000007966159,0.00001671702,0.0004345544,0.0000125726,0.004455665],"genre_scores_gemma":[0.9989587,0.00001908044,0.0002914554,0.00001535179,0.000003589321,0.000007515475,0.0002017678,0.000004951377,0.0004975571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03497934,"threshold_uncertainty_score":0.06955147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2296307188357931,"score_gpt":0.3838593657387171,"score_spread":0.154228646902924,"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."}}