{"id":"W2296703446","doi":"10.14778/2733004.2733009","title":"TPC-DI","year":2014,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Database Systems and Queries","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Master data; Data warehouse; Variety (cybernetics); Data integration; Enterprise data management; Data management; Context (archaeology); Data science; Analytics; Business intelligence; Database; Enterprise information system","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":[0.006941783,0.001604987,0.001267329,0.003791661,0.002264258,0.009134666,0.004887708,0.002656571,0.1248158],"category_scores_gemma":[0.01658285,0.0008613786,0.0006813039,0.005635035,0.0008406202,0.0059934,0.005385824,0.004110058,0.1161589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005099148,"about_ca_system_score_gemma":0.009570589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01548752,"about_ca_topic_score_gemma":0.008852303,"domain_scores_codex":[0.9907668,0.00120075,0.0004622287,0.001403649,0.004890568,0.001276116],"domain_scores_gemma":[0.9750421,0.001545112,0.000493363,0.005772541,0.0127201,0.004426748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007983202,0.0005217938,0.00195341,0.0002493552,0.00003026037,0.0001364402,0.0001593814,0.00141754,0.004816961,0.01972602,0.8157395,0.1544509],"study_design_scores_gemma":[0.0001977049,0.0002918278,0.002594784,0.00008864598,0.00001729363,0.0003113443,0.0001198031,0.01124215,0.007570408,0.004319717,0.9731886,0.00005774128],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01397911,0.001571549,0.09517548,0.005543503,0.003515287,0.002884424,0.06193112,0.108281,0.7071185],"genre_scores_gemma":[0.1062742,0.001380726,0.1445947,0.004662905,0.001273573,0.002916044,0.3662708,0.0249355,0.3476917],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1248158,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006928866262876887,"score_gpt":0.2013198379173866,"score_spread":0.1943909716545097,"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."}}