{"id":"W2516718098","doi":"10.1145/2883616","title":"Unifying Data and Constraint Repairs","year":2016,"lang":"en","type":"article","venue":"Journal of Data and Information Quality","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Data integrity; Data quality; Constraint (computer-aided design); Scalability; Set (abstract data type); Data mining; Semantics (computer science); Data type; Data modeling; Quality (philosophy); Database; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01619767,0.002537354,0.002985861,0.005475366,0.001479954,0.006376355,0.009088022,0.003722545,0.004613788],"category_scores_gemma":[0.08203267,0.001684524,0.003843165,0.006112706,0.003289207,0.01512703,0.007227059,0.004233909,0.0009097249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004236169,"about_ca_system_score_gemma":0.004460956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01248793,"about_ca_topic_score_gemma":0.01066636,"domain_scores_codex":[0.9759837,0.006108108,0.002873556,0.004909281,0.00883339,0.001292097],"domain_scores_gemma":[0.9394224,0.02815418,0.007101059,0.01588883,0.008328592,0.001105012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003759437,0.0001958787,0.007099397,0.0007543031,0.0003816018,0.0004056256,0.0007785801,0.5699845,0.002027823,0.1352055,0.005626826,0.277164],"study_design_scores_gemma":[0.00003785919,0.0001166817,0.0007608439,0.0001017139,0.00009993762,0.000277464,0.0002203022,0.8763836,0.003074681,0.109442,0.009425591,0.00005922853],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01183543,0.000630103,0.9824901,0.0007082358,0.0001114318,0.0002575235,0.0007580153,0.001610146,0.001599072],"genre_scores_gemma":[0.1936479,0.0005449021,0.7993613,0.0003162349,0.0001229708,0.0004530305,0.002106388,0.0008393119,0.002607861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01619767,"threshold_uncertainty_score":0.08566248,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4241185632103378,"score_gpt":0.4856853147821305,"score_spread":0.0615667515717927,"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."}}