{"id":"W4409077140","doi":"10.1109/tbdata.2025.3556615","title":"Utility-Driven Data Analytics Algorithm for Transaction Modifications Using Pre-Large Concept With Single Database Scan","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Big Data","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Database transaction; Analytics; Database; Transaction processing; Data mining; Transaction data; Algorithm; Transaction log; Distributed transaction","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000442475,0.0002553634,0.0002582278,0.0003424941,0.0007031988,0.0002570059,0.003051394,0.0001043501,0.00000533971],"category_scores_gemma":[0.00004692887,0.0002489482,0.00004835842,0.001045681,0.000136968,0.001323324,0.00004426861,0.0002852978,0.000002107343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008550451,"about_ca_system_score_gemma":0.0004148325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003477154,"about_ca_topic_score_gemma":0.0003061385,"domain_scores_codex":[0.997641,0.00009026498,0.0003723365,0.001205758,0.0003068527,0.000383778],"domain_scores_gemma":[0.9933206,0.0004672997,0.000124138,0.005792076,0.0001869223,0.0001089193],"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":[0.00005056488,0.00136436,0.00002802073,0.0000733205,0.0002129671,0.00000517989,0.0002023866,0.004781262,0.0006180368,0.0001683664,0.009364096,0.9831314],"study_design_scores_gemma":[0.0005851764,0.0001033081,0.00003625224,0.0001823315,0.0001968158,0.00001542302,0.00001572079,0.990149,0.004505624,0.0003057851,0.003640467,0.0002641276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001076262,0.00005022339,0.9849747,0.0003105777,0.0005897622,0.0005964316,0.01088537,0.002453196,0.00003209601],"genre_scores_gemma":[0.3086544,0.0000186274,0.6898686,0.0001607194,0.00005059634,0.00003560133,0.001075863,0.0000222674,0.0001133286],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9853677,"threshold_uncertainty_score":0.9999963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2046491776236223,"score_gpt":0.3506634177596448,"score_spread":0.1460142401360225,"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."}}