{"id":"W10845949","doi":"","title":"An Effective and Efficient Data Cleaning Technique in Large Databases.","year":2004,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Database; Computer science","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":[0.009343783,0.00009071516,0.0001588023,0.0002276169,0.00008960273,0.0001850353,0.001044651,0.00002501992,0.000115449],"category_scores_gemma":[0.001128484,0.00006610814,0.0000110501,0.0005007648,0.00005754931,0.000816547,0.001533477,0.0001057037,0.00009119973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003021731,"about_ca_system_score_gemma":0.00001914287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006649242,"about_ca_topic_score_gemma":0.002544779,"domain_scores_codex":[0.9980008,0.0002084802,0.0003154472,0.0007125457,0.0005459243,0.0002167966],"domain_scores_gemma":[0.9977437,0.0003542941,0.00006217228,0.001727704,0.00003068943,0.00008142945],"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":[0.0001132853,0.001928705,0.008760975,0.00004125109,0.00002322186,0.0001589222,0.001947446,0.002368898,0.001932073,0.7152196,0.007644174,0.2598614],"study_design_scores_gemma":[0.009884334,0.0009816596,0.3586591,0.0004043073,0.00006729423,0.00005971448,0.03247759,0.07119951,0.01544348,0.09477736,0.4139607,0.002084966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1383008,0.0000394325,0.8545724,0.0004443007,0.00008431367,0.0008079723,0.000400745,0.00007443019,0.005275641],"genre_scores_gemma":[0.9840086,0.000007134078,0.01516305,0.000569009,0.00001591891,0.00002259519,0.000156335,0.000005077845,0.00005227358],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8457078,"threshold_uncertainty_score":0.3238387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1754386513185937,"score_gpt":0.4672611410951992,"score_spread":0.2918224897766055,"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."}}