{"id":"W1519655831","doi":"10.1007/11523468_84","title":"A Better Approximation Ratio for the Vertex Cover Problem","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":114,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Cover (algebra); Combinatorics; Vertex cover; Mathematics; Relaxation (psychology); Vertex (graph theory); Binary logarithm; Approximation algorithm; Discrete mathematics; 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":[0.001000996,0.0004666145,0.0003928866,0.0004334112,0.0005929256,0.0009209684,0.003741557,0.0002383069,0.0000344756],"category_scores_gemma":[0.00005893829,0.0003439991,0.0002132786,0.0005095604,0.0006741732,0.0007866772,0.0009303074,0.0006462434,0.00004903507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002055628,"about_ca_system_score_gemma":0.0003591109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008582902,"about_ca_topic_score_gemma":0.00003986694,"domain_scores_codex":[0.9967317,0.00002682899,0.0005032895,0.001243726,0.0008840444,0.0006104329],"domain_scores_gemma":[0.9968575,0.001125052,0.0002733263,0.001388126,0.0002621821,0.00009382511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004706895,0.00002208614,0.000003852768,0.00003098115,0.00001536607,0.000003928993,0.0005508894,0.02010213,0.00002802292,0.112565,0.0002503845,0.8664227],"study_design_scores_gemma":[0.000222512,0.00007996363,0.00002620957,0.0001088405,0.000008824654,0.00002294653,6.845559e-8,0.6735702,0.0002746866,0.3079307,0.01741406,0.0003409768],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000004992663,0.0004143413,0.9896368,0.005186647,0.001455832,0.001157255,0.00001014691,0.0001398344,0.001994165],"genre_scores_gemma":[0.00907398,0.00004289255,0.9828745,0.005857762,0.001095978,0.0001023892,0.00001127696,0.00003796741,0.0009032214],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8660817,"threshold_uncertainty_score":0.9999012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02102852362307598,"score_gpt":0.2414040172628108,"score_spread":0.2203754936397349,"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."}}