{"id":"W2141156487","doi":"10.1145/2650183","title":"Approximating Rooted Steiner Networks","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Steiner tree problem; Combinatorics; Mathematics; Generalization; Undirected graph; Linear programming relaxation; Approximation algorithm; Discrete mathematics; Upper and lower bounds; Linear programming; Graph; Mathematical optimization","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":[0.001373202,0.0009756539,0.001094986,0.0009565181,0.0006406549,0.002022613,0.002379028,0.001334097,0.006170398],"category_scores_gemma":[0.01362453,0.0007790649,0.0009327902,0.001860473,0.001043446,0.005006231,0.002477654,0.002390206,0.0008086868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002138964,"about_ca_system_score_gemma":0.0009196308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002215688,"about_ca_topic_score_gemma":0.003447423,"domain_scores_codex":[0.9981999,0.0005692142,0.00008270569,0.0004121346,0.0004791775,0.0002567365],"domain_scores_gemma":[0.9928709,0.005039951,0.0005517781,0.0007824412,0.0004456131,0.0003093852],"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":[0.0003595164,0.0001346596,0.001770526,0.0004136193,0.00007194796,0.0001572843,0.0002930739,0.7783766,0.003751742,0.1370578,0.009215138,0.06839809],"study_design_scores_gemma":[0.00003052878,0.00004055414,0.000355407,0.00003473669,0.0000202597,0.00009708486,0.00008364674,0.8713279,0.001030321,0.1236541,0.003316059,0.000009277849],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1351938,0.001588075,0.8320507,0.001874367,0.0001165759,0.0001355899,0.0011358,0.001037856,0.02686724],"genre_scores_gemma":[0.7053896,0.001503574,0.2821474,0.0004279136,0.0001569251,0.0002094254,0.00218016,0.0003903871,0.007594544],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006170398,"threshold_uncertainty_score":0.02064204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929136036591119,"score_gpt":0.2397969814353036,"score_spread":0.2205056210693924,"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."}}