{"id":"W2087455919","doi":"10.1007/s10878-008-9150-4","title":"Packing trees in communication networks","year":2008,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Canadian Imperial Bank of Commerce (Canada); McMaster University","funders":"","keywords":"Mathematics; Solver; Linear programming relaxation; Approximation algorithm; Multicast; Integer programming; Theory of computation; Steiner tree problem; Combinatorics; Spanning tree; Relaxation (psychology); Tree (set theory); Independent set; Block (permutation group theory); Time complexity; k-minimum spanning tree; Linear programming; Discrete mathematics; Graph; Computer science; Mathematical optimization; Algorithm; Tree structure; Binary tree; K-ary tree","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008363646,0.0000772336,0.0001813514,0.0003031833,0.0001225969,0.00005275671,0.0007739884,0.0000658666,0.000005585826],"category_scores_gemma":[0.0002238518,0.00007316235,0.00005776122,0.0007930225,0.00005732155,0.001244874,0.0001126474,0.0003148542,9.104818e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009798651,"about_ca_system_score_gemma":0.00008734258,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002964275,"about_ca_topic_score_gemma":6.564769e-7,"domain_scores_codex":[0.9986621,0.0003012613,0.00043085,0.00009229078,0.0003530293,0.0001604983],"domain_scores_gemma":[0.9986755,0.0002329308,0.0003592787,0.0003022758,0.0003659027,0.00006408573],"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":[0.00004689994,0.00008469422,0.001565825,9.76576e-7,0.000006261832,0.00002097245,0.0003124467,0.9299923,0.00002513458,0.06682894,0.00008968511,0.001025827],"study_design_scores_gemma":[0.002174216,0.0002378429,0.002264671,0.00007024759,0.000003374107,0.0001209714,0.00003209698,0.9406192,0.0002328576,0.05389963,0.0002063819,0.0001385274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009668251,0.0003984465,0.9882054,0.0002967084,0.000893852,0.00008432178,7.538917e-8,0.00001897761,0.0004340121],"genre_scores_gemma":[0.8893855,0.0006804725,0.1097901,0.00002372148,0.00009969281,0.000001619096,9.649016e-7,0.00000738845,0.00001057334],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8797172,"threshold_uncertainty_score":0.2983474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01893529126758242,"score_gpt":0.2744476154568449,"score_spread":0.2555123241892625,"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."}}