{"id":"W2024836278","doi":"10.1142/s1793830912500085","title":"BOUNDED SEARCH TREE ALGORITHMS FOR PARAMETRIZED COGRAPH DELETION: EFFICIENT BRANCHING RULES BY EXPLOITING STRUCTURES OF SPECIAL GRAPH CLASSES","year":2012,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Bounded function; Mathematics; Algorithm; Vertex (graph theory); Combinatorics; Treewidth; Tree-depth; Graph; Discrete mathematics; Theoretical computer science; Computer science; Pathwidth; Line graph","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006911787,0.000310329,0.0004706272,0.0003076465,0.0006917797,0.0003107311,0.0007000445,0.0001114002,0.00001134597],"category_scores_gemma":[0.00005331062,0.0002816862,0.0002427585,0.0008635105,0.0003273821,0.0002955667,0.0002463399,0.0002019795,0.000002548954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002346748,"about_ca_system_score_gemma":0.00003595034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000176382,"about_ca_topic_score_gemma":0.000001729478,"domain_scores_codex":[0.9977067,0.00005320377,0.0006682532,0.0004772442,0.0005099708,0.0005846084],"domain_scores_gemma":[0.9979565,0.0007031219,0.0003160282,0.0005957137,0.0001973706,0.0002312903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000619125,0.0004420167,0.00006002603,0.000264804,0.000113685,2.559173e-7,0.002451633,0.00007770349,0.0009350918,0.8530604,0.0002095543,0.1423786],"study_design_scores_gemma":[0.002124767,0.0002051268,0.0007747399,0.0001457561,0.0001633273,0.00004997826,0.003758149,0.5083715,0.009663441,0.46571,0.007882068,0.001151078],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0239535,0.0007724985,0.9730456,0.0001845745,0.0001561937,0.001088055,0.0002809069,0.0001126128,0.000406033],"genre_scores_gemma":[0.1443734,0.000148469,0.8540455,0.00004904328,0.0006564842,0.0005451599,0.0001187162,0.00003683556,0.00002650144],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5082938,"threshold_uncertainty_score":0.9999635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03785958332532282,"score_gpt":0.3017967662122005,"score_spread":0.2639371828868777,"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."}}