{"id":"W2131850161","doi":"10.1007/978-3-319-15579-1_53","title":"Bounding Clique-Width via Perfect Graphs","year":2015,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Simon Fraser University","keywords":"Combinatorics; Mathematics; Treewidth; Split graph; Block graph; Cograph; Discrete mathematics; Clique-sum; Chordal graph; Bounding overwatch; Induced subgraph; Graph isomorphism; Induced subgraph isomorphism problem; Perfect graph; Pathwidth; Graph; Line graph; 1-planar graph; Computer science; Vertex (graph theory); Voltage graph","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":[0.00470987,0.002064711,0.002328427,0.00273742,0.001814929,0.004870363,0.006027848,0.003129648,0.008935919],"category_scores_gemma":[0.04405144,0.002372694,0.001853989,0.003391919,0.004110411,0.01531957,0.007480418,0.005541846,0.001201629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002820938,"about_ca_system_score_gemma":0.001649339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00248555,"about_ca_topic_score_gemma":0.003607245,"domain_scores_codex":[0.994233,0.001575417,0.0001706349,0.001737751,0.001418877,0.0008643668],"domain_scores_gemma":[0.9594777,0.03146523,0.001758653,0.004247675,0.001166385,0.001884298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009952973,0.0002828874,0.005361577,0.0008018219,0.0002446087,0.0002219273,0.0006282466,0.2025098,0.007522208,0.695751,0.02159061,0.06408995],"study_design_scores_gemma":[0.00005938193,0.00004617178,0.0005854605,0.00005054002,0.00005810984,0.0001093485,0.00007626812,0.3315342,0.001801963,0.6626064,0.003049033,0.00002308037],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1824265,0.00292847,0.7573389,0.006385319,0.0004694036,0.0002019967,0.002262298,0.00246943,0.04551768],"genre_scores_gemma":[0.8332813,0.001721029,0.1502648,0.001006232,0.0008690805,0.0002989344,0.001581441,0.0009554523,0.01002177],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008935919,"threshold_uncertainty_score":0.02989364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03181572665495894,"score_gpt":0.3255480907228837,"score_spread":0.2937323640679247,"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."}}