{"id":"W3178051994","doi":"10.3934/jimo.2021116","title":"Approximation algorithm with constant ratio for stochastic prize-collecting Steiner tree problem","year":2021,"lang":"en","type":"article","venue":"Journal of Industrial and Management Optimization","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Steiner tree problem; Stochastic optimization; Mathematical optimization; Computer science; Stochastic programming; Tree (set theory); Constant (computer programming); Approximation algorithm; Optimization problem; Mathematics; Combinatorics","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":[0.002453666,0.001756188,0.002944659,0.001069647,0.001001239,0.002189622,0.003438825,0.002191926,0.00776534],"category_scores_gemma":[0.00620947,0.0006479748,0.001570021,0.002161667,0.0008987285,0.003010453,0.002391416,0.002793665,0.001385742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002527889,"about_ca_system_score_gemma":0.003178263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004516552,"about_ca_topic_score_gemma":0.004609786,"domain_scores_codex":[0.998266,0.0006351906,0.00006763628,0.0002868215,0.0003000943,0.0004443112],"domain_scores_gemma":[0.9972289,0.0017914,0.0002394702,0.000251776,0.000257139,0.0002313683],"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":[0.0006461613,0.0004436449,0.001333341,0.000471127,0.0001153118,0.0001775002,0.000210251,0.827352,0.001572427,0.05468775,0.01841391,0.09457655],"study_design_scores_gemma":[0.00006634985,0.00005898431,0.0001131872,0.00001998111,0.00001867709,0.00006362215,0.00004169356,0.9751738,0.0002182235,0.02305395,0.001162182,0.000009299223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04230188,0.001724967,0.9396133,0.00161927,0.000259485,0.0003077102,0.000528693,0.001123573,0.01252104],"genre_scores_gemma":[0.4419609,0.001074648,0.5464833,0.0007480743,0.0002631981,0.0006321588,0.001372384,0.0004502645,0.007015056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00776534,"threshold_uncertainty_score":0.02597767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03790861511359168,"score_gpt":0.2395858142667586,"score_spread":0.201677199153167,"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."}}