{"id":"W2067393160","doi":"10.4018/ijirr.2013100107","title":"Interactive Visual Analytics of Databases and Frequent Sets","year":2013,"lang":"en","type":"article","venue":"International Journal of Information Retrieval Research","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Visual analytics; Database transaction; Set (abstract data type); Database; Visualization; Information retrieval; Analytics; Data mining; Interactive visual 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":[0.001803039,0.00114782,0.00062501,0.004869159,0.000561679,0.003923399,0.001222763,0.0008878683,0.01359498],"category_scores_gemma":[0.01000329,0.0005046512,0.000829249,0.003279683,0.001020313,0.004470275,0.003599175,0.001103134,0.001937387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005910838,"about_ca_system_score_gemma":0.0005021321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00131209,"about_ca_topic_score_gemma":0.001108624,"domain_scores_codex":[0.9987446,0.0004371557,0.0001000155,0.0001979346,0.000448126,0.00007214062],"domain_scores_gemma":[0.9938524,0.004507101,0.0003780843,0.0004416268,0.0006464191,0.0001744586],"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":[0.001386826,0.0001940548,0.003608425,0.003154515,0.0001851508,0.001507842,0.00741016,0.02800692,0.02769459,0.1930565,0.07004885,0.6637461],"study_design_scores_gemma":[0.0002224679,0.0002626773,0.004215691,0.001034021,0.0001105406,0.002523681,0.003517945,0.2810632,0.01815987,0.4691556,0.2195182,0.0002160414],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01967369,0.002384625,0.9473962,0.001826957,0.0002634757,0.0002710027,0.002368122,0.01049611,0.01531979],"genre_scores_gemma":[0.2082326,0.00324599,0.7778637,0.0005300847,0.0004348296,0.0005725373,0.002962429,0.0009700294,0.005187781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01359498,"threshold_uncertainty_score":0.04547977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06121063490723716,"score_gpt":0.4204395344302275,"score_spread":0.3592288995229904,"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."}}