{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004569243,0.0002495109,0.0002506489,0.0002118492,0.0005127229,0.0002183078,0.001539402,0.0001203859,0.00006328025],"category_scores_gemma":[0.00004959166,0.0002385821,0.0001762361,0.0008808824,0.00008091196,0.0004251334,0.00004203039,0.0004859903,0.00008207116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003771748,"about_ca_system_score_gemma":0.00002251427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003983943,"about_ca_topic_score_gemma":0.00001293976,"domain_scores_codex":[0.9981105,0.0001312158,0.0003601066,0.0005640332,0.0003689126,0.0004651892],"domain_scores_gemma":[0.9978418,0.0003567402,0.00009557614,0.001461897,0.00008271754,0.0001612061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003457739,0.0001393439,0.000005966927,0.000006618673,0.00003050602,0.000003278252,0.0001365537,0.01966012,0.0000270413,0.007915587,0.000076608,0.9719949],"study_design_scores_gemma":[0.0004787929,0.000168775,0.0003316558,0.00003248665,0.00001243535,0.0000268582,0.00002051551,0.9787567,0.0005755624,0.01472946,0.004543316,0.0003235016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003890121,0.00003985831,0.9952475,0.001161289,0.001010345,0.0001694367,0.000003868588,0.000615604,0.001363018],"genre_scores_gemma":[0.2867214,0.00001767595,0.7117873,0.0007607356,0.00021818,0.00005612638,0.00000413823,0.00002674277,0.0004077293],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9716714,"threshold_uncertainty_score":0.9729097,"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."}}