{"id":"W7132886178","doi":"","title":"Iterative improvement of database configurations","year":2006,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada; Library and Archives Canada","funders":"","keywords":"Iterative and incremental development; Process (computing); Class (philosophy); Control (management); Iterative method; Big data; Recommender system; Materialized view","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":[0.0002877383,0.0005977273,0.0007677575,0.000261086,0.0003615099,0.0001141444,0.0005723591,0.0001932571,0.0002797358],"category_scores_gemma":[0.00009391405,0.0005925797,0.0001948048,0.0006106241,0.0001565893,0.00110447,0.0001947085,0.0003636805,0.00006876256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009271099,"about_ca_system_score_gemma":0.0005903437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003965153,"about_ca_topic_score_gemma":0.001419569,"domain_scores_codex":[0.9965966,0.0001040756,0.001121332,0.0009910336,0.0007059613,0.0004809908],"domain_scores_gemma":[0.9958622,0.0001638837,0.001413403,0.00156412,0.0008470941,0.0001492824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001111874,0.0005053059,0.00003328429,0.001563751,0.000204581,0.00005118186,0.02844798,0.0004316413,0.5217112,0.4218231,0.006458549,0.0186582],"study_design_scores_gemma":[0.002149653,0.001364186,0.0009981013,0.00331702,0.0002666816,0.00002195784,0.0286615,0.02099288,0.7918364,0.0004252495,0.1475212,0.002445206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02277374,0.001274441,0.954069,0.0001946172,0.002061252,0.001332232,0.001232027,0.00007671075,0.01698604],"genre_scores_gemma":[0.4105864,0.0007088589,0.3196505,0.0003424085,0.001331988,0.0008980036,0.03973821,0.000242189,0.2265014],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6344184,"threshold_uncertainty_score":0.9996526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01938271900128443,"score_gpt":0.3331789206777541,"score_spread":0.3137962016764697,"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."}}