{"id":"W2095338002","doi":"10.1002/(sici)1520-6750(200006)47:4<287::aid-nav2>3.0.co;2-r","title":"Heuristics for the location of inspection stations on a network","year":2000,"lang":"en","type":"article","venue":"Naval Research Logistics (NRL)","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Imperial Oil (Canada); HEC Montréal; Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Heuristics; Tabu search; Heuristic; Computer science; Mathematical optimization; Path (computing); Flow network; Greedy algorithm; Reduction (mathematics); Operations research; Artificial intelligence; Mathematics; Algorithm; Computer network","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":[0.001628322,0.001039219,0.000911775,0.001840281,0.0007470805,0.001281245,0.001431044,0.001193799,0.002664187],"category_scores_gemma":[0.004916619,0.0008835286,0.0006418488,0.001861936,0.0009930587,0.001181041,0.0008520968,0.0006832018,0.0004622963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001724567,"about_ca_system_score_gemma":0.00202197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008540005,"about_ca_topic_score_gemma":0.01131478,"domain_scores_codex":[0.9990723,0.0005021485,0.00003937622,0.0001115628,0.0001408954,0.0001336842],"domain_scores_gemma":[0.9979571,0.001505568,0.0002111098,0.0001173033,0.0001377183,0.00007106812],"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":[0.00008538817,0.00003391982,0.0004891777,0.0001050933,0.00003700982,0.0000759774,0.000079948,0.9461721,0.0004759869,0.01173275,0.001798801,0.03891381],"study_design_scores_gemma":[0.00008627918,0.0000675956,0.0002534883,0.00003927794,0.00004013185,0.00007221294,0.00008367666,0.9779744,0.0007112129,0.01692423,0.003731078,0.00001641523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06769042,0.001918962,0.9207838,0.0003240092,0.00007109783,0.0003214105,0.0002497956,0.00109048,0.007549993],"genre_scores_gemma":[0.397649,0.001401827,0.5972588,0.0001034291,0.00004347454,0.0003362029,0.0004461568,0.00011341,0.002647765],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008540005,"threshold_uncertainty_score":0.01698059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1918134376875431,"score_gpt":0.3842398050949423,"score_spread":0.1924263674073991,"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."}}