{"id":"W2122238195","doi":"10.1016/j.ejc.2009.11.008","title":"An improved linear bound on the number of perfect matchings in cubic graphs","year":2009,"lang":"en","type":"article","venue":"European Journal of Combinatorics","topic":"Advanced Graph Theory Research","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Combinatorics; Mathematics; Cubic graph; Perfect graph theorem; Polytope; Matching (statistics); Perfect graph; Trivially perfect graph; Dimension (graph theory); Graph; Upper and lower bounds; Discrete mathematics; Line graph; Pathwidth; Mathematical analysis","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":[0.004852087,0.003723394,0.003901251,0.003821596,0.003057924,0.01029207,0.01053773,0.004473877,0.04789815],"category_scores_gemma":[0.02954782,0.00222123,0.003157985,0.00656993,0.00388159,0.02272055,0.009821653,0.009096054,0.0115313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008468756,"about_ca_system_score_gemma":0.005795266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006142919,"about_ca_topic_score_gemma":0.01107004,"domain_scores_codex":[0.9912295,0.001451654,0.000331171,0.001798283,0.002994083,0.002195326],"domain_scores_gemma":[0.9650843,0.02456783,0.00103666,0.005476458,0.001950724,0.001884059],"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":[0.007558919,0.002011167,0.007252506,0.004496317,0.0006074324,0.0009449631,0.0009650079,0.1975946,0.04282602,0.2815165,0.1524743,0.3017522],"study_design_scores_gemma":[0.0006748696,0.0005061078,0.002700927,0.0003103149,0.0005314332,0.0005670554,0.0002834051,0.5064681,0.01536156,0.4432455,0.02913795,0.0002126695],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2041208,0.01496237,0.4510334,0.0265358,0.004340289,0.0007983096,0.01225437,0.01363366,0.2723209],"genre_scores_gemma":[0.7017838,0.006774182,0.2050244,0.005652887,0.004886489,0.000987947,0.007640252,0.00306054,0.06418949],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04789815,"threshold_uncertainty_score":0.1602352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631360234602767,"score_gpt":0.2919061411560183,"score_spread":0.2755925388099906,"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."}}