{"id":"W4327590965","doi":"10.1007/s10115-023-01850-5","title":"Towards intelligent database systems using clusters of SQL transactions","year":2023,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Online transaction processing; Troubleshooting; Database transaction; Database; DBSCAN; Credit card; Cluster analysis; Transaction processing; Data mining; SQL; Overhead (engineering); Artificial intelligence; Operating system; World Wide Web","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":[0.0005999601,0.0001467911,0.000275165,0.0003972276,0.0001758348,0.0001245667,0.0002139295,0.00006105143,0.000002217363],"category_scores_gemma":[0.00002382773,0.0001265629,0.00004866007,0.0007919483,0.00004606682,0.00506012,0.00009992059,0.0000789009,0.0001110541],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005852752,"about_ca_system_score_gemma":0.000105028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003169609,"about_ca_topic_score_gemma":0.000007248711,"domain_scores_codex":[0.9985809,0.00007776462,0.0007301868,0.0001550951,0.000239393,0.0002166477],"domain_scores_gemma":[0.9988875,0.00005777676,0.0002551157,0.0004399391,0.0002534041,0.0001062674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004316806,0.0001117718,0.000194094,0.009815745,0.0002454618,0.00001048703,0.04949016,0.0645797,0.001773871,0.7699696,0.006608514,0.09715738],"study_design_scores_gemma":[0.000229275,0.00003505613,0.00003578181,0.000364941,0.000008945668,0.00005656521,0.00364615,0.7215192,0.0004878613,0.000005441116,0.2734362,0.0001746366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00288504,0.001013148,0.9904703,0.00001868521,0.002037857,0.0004087677,0.0001675827,0.0001924173,0.002806228],"genre_scores_gemma":[0.9942136,0.0004996061,0.004357785,0.00002346844,0.0001428978,0.00009123118,0.0001583845,0.00001408582,0.0004988835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9913286,"threshold_uncertainty_score":0.5161083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03683546323027916,"score_gpt":0.2875389323398121,"score_spread":0.250703469109533,"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."}}