{"id":"W2096281132","doi":"10.1145/1460797.1460799","title":"Mining frequent cross-graph quasi-cliques","year":2009,"lang":"en","type":"article","venue":"ACM Transactions on Knowledge Discovery from Data","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Division of Information and Intelligent Systems","keywords":"Heuristics; Computer science; Clique; Data mining; Vertex (graph theory); Graph; Theoretical computer science; Combinatorics; Mathematics","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":[0.002263108,0.000797415,0.001630815,0.002742835,0.001765262,0.001966204,0.002569589,0.001500838,0.002296163],"category_scores_gemma":[0.01356022,0.001116731,0.001859942,0.003231357,0.001189523,0.005258562,0.002143375,0.001442086,0.0003954698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009719478,"about_ca_system_score_gemma":0.001221006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003856919,"about_ca_topic_score_gemma":0.005440415,"domain_scores_codex":[0.9969391,0.0007934471,0.0001690102,0.001225605,0.0005564271,0.0003164201],"domain_scores_gemma":[0.9824293,0.01115739,0.002299686,0.001914452,0.001502833,0.0006963699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001332821,0.001216596,0.1023359,0.001956437,0.001693472,0.005463622,0.002171993,0.4789174,0.02022272,0.1849571,0.0280882,0.1716437],"study_design_scores_gemma":[0.00007655209,0.00008587109,0.006340689,0.00005856347,0.00009082631,0.0009850245,0.0005107828,0.8424877,0.002494572,0.1420558,0.00477494,0.00003852961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4464625,0.001082401,0.540214,0.002123375,0.00006974472,0.0004135698,0.005588637,0.0008243404,0.00322147],"genre_scores_gemma":[0.7608451,0.0005047754,0.2262318,0.0003565323,0.0001522936,0.0002988084,0.009530523,0.0001513126,0.001928922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003856919,"threshold_uncertainty_score":0.01196861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05441437221485232,"score_gpt":0.3372334490668411,"score_spread":0.2828190768519887,"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."}}