{"id":"W2149458512","doi":"10.1007/978-3-642-21458-5_35","title":"Approximation Algorithms for Orienting Mixed Graphs","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Logarithm; Computer science; Undirected graph; Approximation algorithm; Graph; Vertex (graph theory); Directed graph; Block graph; Combinatorics; Algorithm; Discrete mathematics; Line graph; Mathematics; Theoretical computer science; Pathwidth","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":[0.001160701,0.002367229,0.001906295,0.002137802,0.001037301,0.003738463,0.004546116,0.001888124,0.01389695],"category_scores_gemma":[0.006514659,0.001328601,0.001954118,0.004789791,0.001128033,0.007730599,0.003347615,0.004161554,0.003144665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002255303,"about_ca_system_score_gemma":0.001119926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002720014,"about_ca_topic_score_gemma":0.004070646,"domain_scores_codex":[0.9987607,0.0003029273,0.00007557396,0.0002843381,0.0003923914,0.0001839861],"domain_scores_gemma":[0.9970299,0.001627464,0.0001690622,0.000738424,0.000271951,0.0001631853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006563126,0.0005878698,0.001491286,0.0009809198,0.0001764614,0.0001535969,0.000519233,0.115151,0.005413482,0.2707791,0.04036965,0.5637211],"study_design_scores_gemma":[0.0001997895,0.0001096345,0.0004425557,0.000138284,0.0001331646,0.0002629554,0.0002415338,0.4672373,0.003213831,0.5137214,0.01426631,0.0000333073],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05969884,0.002554479,0.903138,0.0009615694,0.0002851554,0.0002390656,0.0008645456,0.003104697,0.02915365],"genre_scores_gemma":[0.1870684,0.001801924,0.7901967,0.0004003775,0.0002394231,0.0004520281,0.003238734,0.001153668,0.01544876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01389695,"threshold_uncertainty_score":0.04648989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04011783219635234,"score_gpt":0.2884520227007706,"score_spread":0.2483341905044183,"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."}}