{"id":"W2163024037","doi":"10.1109/icdmw.2010.145","title":"Evaluating Association Rules by Quantitative Pairwise Property Comparisons","year":2010,"lang":"en","type":"article","venue":"","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Lethbridge","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pairwise comparison; Association rule learning; Computer science; Analytic hierarchy process; Data mining; Property (philosophy); Task (project management); Measure (data warehouse); Association (psychology); Selection (genetic algorithm); Domain (mathematical analysis); Process (computing); Set (abstract data type); Machine learning; Artificial intelligence; Mathematics; Operations research; Engineering","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":[0.03996407,0.001930223,0.002597211,0.01699702,0.001238658,0.005116457,0.002160629,0.001383206,0.002392379],"category_scores_gemma":[0.1298741,0.0004859035,0.002057871,0.008649847,0.001840104,0.006814141,0.002438458,0.001689442,0.000666797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009727213,"about_ca_system_score_gemma":0.001744811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004607453,"about_ca_topic_score_gemma":0.0006469671,"domain_scores_codex":[0.9542303,0.0201114,0.005943509,0.004116209,0.01499308,0.0006054629],"domain_scores_gemma":[0.8236708,0.1406483,0.01290483,0.00822396,0.01342625,0.001125731],"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":[0.001096747,0.0008240489,0.07000308,0.002412377,0.001729295,0.0006950009,0.001135461,0.100158,0.02568782,0.04079606,0.003256183,0.7522059],"study_design_scores_gemma":[0.0002456511,0.003073996,0.02453857,0.0004387865,0.001062343,0.001697012,0.002105521,0.7078969,0.03782742,0.2127104,0.008039513,0.000363788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09633336,0.001045809,0.8965058,0.0004313966,0.00009032992,0.0006557333,0.000896536,0.0009085439,0.003132431],"genre_scores_gemma":[0.3651063,0.0003487187,0.6321658,0.00007893703,0.00008744284,0.0006142494,0.001195302,0.00008504237,0.0003182291],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03996407,"threshold_uncertainty_score":0.2113527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06888549084155006,"score_gpt":0.359598028990325,"score_spread":0.290712538148775,"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."}}