{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001139729,0.00005843041,0.0001091608,0.0006489212,0.00005101386,0.0003407005,0.0008413905,0.00002506257,0.0000611139],"category_scores_gemma":[0.001117031,0.00004766747,0.00003825428,0.0003868951,0.00009328511,0.004571362,0.0003813587,0.000276137,0.00004689756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008624214,"about_ca_system_score_gemma":0.0001923129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009291768,"about_ca_topic_score_gemma":9.290429e-7,"domain_scores_codex":[0.9979576,0.00005678804,0.0005674978,0.00006882946,0.001224982,0.0001242667],"domain_scores_gemma":[0.9951689,0.0004364341,0.0003888334,0.0001463475,0.003755708,0.0001037961],"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":[0.0001677054,0.0003289208,0.001843455,0.0000485597,0.0003770616,0.00001699936,0.00376258,0.0001603625,0.003578845,0.07240752,0.01776603,0.899542],"study_design_scores_gemma":[0.002881251,0.001388177,0.07505229,0.0006140997,0.00002321125,0.0006882615,0.004607964,0.7919377,0.05153474,0.01360904,0.05720884,0.0004544191],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3500786,0.00009542554,0.641925,0.004955955,0.0005269002,0.0002676456,0.00009758137,0.00001642031,0.002036547],"genre_scores_gemma":[0.9520383,0.0001955559,0.04750534,0.0001191417,0.00006997288,0.000002776809,0.00002670123,0.000002800911,0.00003933894],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8990875,"threshold_uncertainty_score":0.3314127,"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."}}