{"id":"W2913385138","doi":"10.1016/j.dam.2019.01.003","title":"Approximation algorithms for the fault-tolerant facility location problem with penalties","year":2019,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Randomized rounding; Facility location problem; Rounding; Approximation algorithm; Mathematics; Greedy algorithm; Fault tolerance; Algorithm; Mathematical optimization; Computer science; Distributed computing","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":[0.003195689,0.001539415,0.002600522,0.00117265,0.000969941,0.002587503,0.003932597,0.002701143,0.005056305],"category_scores_gemma":[0.01608278,0.00086806,0.00108388,0.002606809,0.00132993,0.004356217,0.002295949,0.003511487,0.0007075193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00333044,"about_ca_system_score_gemma":0.003027431,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008566313,"about_ca_topic_score_gemma":0.00705231,"domain_scores_codex":[0.998221,0.0007383777,0.00008256865,0.0002836237,0.0003251365,0.0003492819],"domain_scores_gemma":[0.9900663,0.007826393,0.0005877122,0.0005982011,0.0005021223,0.0004192941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003684342,0.0001464728,0.0006458198,0.0001582637,0.0000513337,0.0000448493,0.00008237219,0.9181224,0.0002937305,0.03578407,0.004420617,0.03988169],"study_design_scores_gemma":[0.00004321331,0.00002705208,0.00006727001,0.00001157039,0.000009524751,0.00001808023,0.00002133593,0.9746987,0.0001031623,0.02461542,0.0003799092,0.000004748858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02946931,0.001060431,0.9624441,0.001469454,0.0001549045,0.00009592641,0.0002770677,0.0005516942,0.004477117],"genre_scores_gemma":[0.62909,0.001090211,0.36014,0.0004523058,0.0002519698,0.0003394677,0.001025039,0.0003488602,0.007262066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008566313,"threshold_uncertainty_score":0.02416414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0245543813726375,"score_gpt":0.2314811016029586,"score_spread":0.2069267202303211,"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."}}