{"id":"W2171332293","doi":"10.1145/1366102.1366103","title":"Conditional functional dependencies for capturing data inconsistencies","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Database Systems","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":458,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada)","funders":"Engineering and Physical Sciences Research Council","keywords":"Computer science; Functional dependency; Data integrity; Consistency (knowledge bases); Relational database; SQL; Data mining; Set (abstract data type); Schema (genetic algorithms); Database; Programming language; Theoretical computer science; Algorithm; Information retrieval; Artificial intelligence","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":[0.00596049,0.001493781,0.001008972,0.003373366,0.001390214,0.002483564,0.003619769,0.001471629,0.004050264],"category_scores_gemma":[0.03202393,0.001027983,0.001926781,0.003194467,0.002039955,0.007278857,0.003140515,0.003481669,0.0005684242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002176254,"about_ca_system_score_gemma":0.003973315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009169787,"about_ca_topic_score_gemma":0.01112289,"domain_scores_codex":[0.9896253,0.002408356,0.0009249324,0.001820087,0.004562165,0.0006592409],"domain_scores_gemma":[0.9679843,0.01933556,0.002947006,0.005303276,0.004065137,0.0003646371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005351298,0.0003044803,0.02062658,0.001195576,0.0002601479,0.001353596,0.001027788,0.2548094,0.02310361,0.3538506,0.0165431,0.32639],"study_design_scores_gemma":[0.00006227894,0.0001581655,0.002392726,0.0001791995,0.0001457845,0.0009433918,0.0002501449,0.7545909,0.03303646,0.1809362,0.02716524,0.0001395025],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01428972,0.0002522221,0.9796801,0.0004469699,0.0000645448,0.0001877647,0.001089224,0.002497668,0.001491692],"genre_scores_gemma":[0.24742,0.0003318627,0.7472166,0.0005092593,0.00009172968,0.0003356464,0.002207848,0.0005435083,0.001343643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009169787,"threshold_uncertainty_score":0.03152251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5917106512846138,"score_gpt":0.4156652633131301,"score_spread":0.1760453879714837,"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."}}