{"id":"W2112154958","doi":"10.1109/tkde.2009.59","title":"Discovering Transitional Patterns and Their Significant Milestones in Transaction Databases","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Computer science; Database; Database transaction; Transaction processing; Transaction log; Distributed database; Information retrieval; Data science","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":[0.001874686,0.0005650098,0.0007834533,0.00529917,0.001014439,0.002478479,0.001375894,0.0008254159,0.001039653],"category_scores_gemma":[0.01535948,0.0005913836,0.000874859,0.007846926,0.0008078357,0.005282489,0.001762979,0.001009484,0.0006304621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004939896,"about_ca_system_score_gemma":0.0007969668,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001581796,"about_ca_topic_score_gemma":0.001458214,"domain_scores_codex":[0.997512,0.0003789894,0.000471992,0.0006024358,0.000817434,0.0002172556],"domain_scores_gemma":[0.9912859,0.004013802,0.001771474,0.0010865,0.001409929,0.0004324226],"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":[0.001292252,0.0004681887,0.1934094,0.001365282,0.0004896842,0.004846871,0.004728033,0.04818012,0.02151923,0.07274156,0.006982191,0.6439772],"study_design_scores_gemma":[0.0001088586,0.0006383157,0.06763569,0.0004866188,0.0004121987,0.005485123,0.005025877,0.516828,0.02643863,0.3407599,0.03594046,0.0002403855],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3945386,0.002767125,0.5931224,0.0007428871,0.00008689811,0.0003580355,0.003344891,0.00127467,0.003764485],"genre_scores_gemma":[0.7138617,0.001222588,0.2796689,0.0001177128,0.00006020387,0.0003254588,0.003473334,0.00008382412,0.001186399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00529917,"threshold_uncertainty_score":0.009914398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02862650924382022,"score_gpt":0.2647418609200139,"score_spread":0.2361153516761937,"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."}}