{"id":"W2218881374","doi":"","title":"Trusted Data in IBM's Master Data Management","year":2011,"lang":"en","type":"article","venue":"Databases, Knowledge, and Data Applications","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"IBM; Computer science; Master data; Data quality; Quality (philosophy); Data warehouse; Process (computing); Data governance; Data modeling; Database; Process management; Data science; Operating system; Engineering; Operations management","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":[0.01298024,0.0004017469,0.0005806831,0.002064505,0.002023271,0.009590116,0.001121814,0.001292462,0.002052491],"category_scores_gemma":[0.02051728,0.0005851162,0.0005843374,0.004618698,0.003955434,0.01099337,0.003634277,0.003061021,0.0006432793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004565392,"about_ca_system_score_gemma":0.004596551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009819113,"about_ca_topic_score_gemma":0.005346729,"domain_scores_codex":[0.9883537,0.003827398,0.000934582,0.00108004,0.005225598,0.0005787004],"domain_scores_gemma":[0.9892356,0.003671744,0.001457312,0.003015557,0.001933805,0.0006860646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001757556,0.00004804835,0.006370526,0.0001310588,0.0000322115,0.000294323,0.002301353,0.01591186,0.001235865,0.7998043,0.01158764,0.162107],"study_design_scores_gemma":[0.00008015226,0.0001712297,0.002727202,0.0002866063,0.0000741674,0.0005683974,0.001732129,0.1394919,0.007108347,0.634994,0.2126703,0.00009562835],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0914806,0.007340105,0.8116284,0.02909356,0.0006297895,0.0002725927,0.0006240466,0.002558141,0.05637282],"genre_scores_gemma":[0.6754409,0.002823978,0.3095503,0.0009344566,0.0005333201,0.0001644267,0.0004683081,0.0003243783,0.009759937],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01298024,"threshold_uncertainty_score":0.06864691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6106244189975273,"score_gpt":0.4788549332639887,"score_spread":0.1317694857335386,"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."}}