{"id":"W2963443214","doi":"10.1287/ijoc.2018.0869","title":"A Flexible, Natural Formulation for the Network Design Problem with Vulnerability Constraints","year":2019,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Bounded function; Network planning and design; Backup; Mathematical optimization; Mathematics; Enhanced Data Rates for GSM Evolution; Computer science; Benchmark (surveying); Graph; Hop (telecommunications); Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001835654,0.001541856,0.0006619662,0.0007283363,0.0005582322,0.001515618,0.001613654,0.001414951,0.00523635],"category_scores_gemma":[0.005648396,0.0006870804,0.001105209,0.001286979,0.001217139,0.002158149,0.001439082,0.002445138,0.0005133284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00133253,"about_ca_system_score_gemma":0.002273921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002714498,"about_ca_topic_score_gemma":0.006582771,"domain_scores_codex":[0.9986558,0.0005661434,0.00006078088,0.0002928175,0.0003099161,0.0001145325],"domain_scores_gemma":[0.9982625,0.001162085,0.0001758488,0.0001461436,0.0001838861,0.00006957373],"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":[0.00004424504,0.0000993265,0.0003248443,0.0002720255,0.00002352913,0.0001461993,0.00009841932,0.863596,0.001610274,0.1001749,0.005459114,0.0281511],"study_design_scores_gemma":[0.00005324545,0.00008833328,0.0001364695,0.00005459245,0.00001546566,0.000143618,0.00007644061,0.9217994,0.0006795052,0.06649879,0.01043628,0.00001779819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005917998,0.0001389196,0.9887065,0.0004554622,0.0000569064,0.0001417395,0.000274287,0.00007712458,0.004231132],"genre_scores_gemma":[0.1122769,0.0003735768,0.8816378,0.0002898966,0.00008900178,0.0007404529,0.0005513889,0.0001185773,0.003922496],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00523635,"threshold_uncertainty_score":0.01751739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02312016732893144,"score_gpt":0.2737438699909489,"score_spread":0.2506237026620174,"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."}}