{"id":"W2169474320","doi":"10.1109/ideas.2003.1214917","title":"Incremental mining of frequent patterns without candidate generation or support constraint","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":216,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Constraint (computer-aided design); Data mining; Tree (set theory); Tree structure; Binary tree; Algorithm; Engineering; 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":[0.001432076,0.0004723834,0.001019957,0.002246292,0.0005970101,0.001182154,0.002126653,0.0006924628,0.001255584],"category_scores_gemma":[0.01186994,0.0004740657,0.0008609847,0.002672651,0.0003781389,0.003276031,0.001127635,0.0007380983,0.0006882698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002678097,"about_ca_system_score_gemma":0.0012262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001081538,"about_ca_topic_score_gemma":0.001963685,"domain_scores_codex":[0.9985321,0.0002527769,0.0001639465,0.0002348237,0.0007153237,0.0001011474],"domain_scores_gemma":[0.9909397,0.005519658,0.0005312313,0.001122007,0.001689669,0.0001976885],"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":[0.0008434816,0.0004110382,0.0147226,0.0006692452,0.0002667585,0.001667637,0.0003613333,0.02927555,0.02599532,0.01215893,0.00674951,0.9068785],"study_design_scores_gemma":[0.0002490384,0.0009551772,0.006432623,0.0001454426,0.0004595139,0.003579644,0.000386375,0.8815486,0.04092842,0.04427118,0.02094423,0.00009987576],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1101384,0.0008930831,0.8838767,0.0003322701,0.0001057463,0.0003339888,0.0009521928,0.001546583,0.001821116],"genre_scores_gemma":[0.2848112,0.0004471237,0.7094833,0.0001644032,0.0001124696,0.0003062897,0.003328128,0.00009485344,0.001252346],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002246292,"threshold_uncertainty_score":0.007573605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0403410905032692,"score_gpt":0.284965270308043,"score_spread":0.2446241798047738,"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."}}