{"id":"W2726342193","doi":"10.1145/3041761","title":"Dependable Data Repairing with Fixing Rules","year":2017,"lang":"en","type":"article","venue":"Journal of Data and Information Quality","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Tuple; Data mining; Set (abstract data type); Data integrity; Class (philosophy); Artificial intelligence; Database","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":[0.01049036,0.001795226,0.002042043,0.004519955,0.00188582,0.003534477,0.005688857,0.002823173,0.002144727],"category_scores_gemma":[0.06757914,0.001466909,0.003718339,0.003406347,0.003183718,0.005229757,0.004463663,0.00403516,0.001024441],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001350474,"about_ca_system_score_gemma":0.003630694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005096319,"about_ca_topic_score_gemma":0.00471744,"domain_scores_codex":[0.9829055,0.00378684,0.002241965,0.004332307,0.005942374,0.0007910266],"domain_scores_gemma":[0.9244609,0.03783238,0.007519656,0.021432,0.008228188,0.0005268757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003551353,0.0004389968,0.0152276,0.0008381406,0.0004632249,0.00131361,0.001093084,0.2949863,0.01886375,0.04008886,0.008919382,0.6174118],"study_design_scores_gemma":[0.00008391734,0.0001974949,0.002090101,0.0002622764,0.0002731972,0.001296507,0.0003671676,0.8143592,0.0494641,0.1153916,0.01606319,0.0001511511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01484999,0.0002506442,0.9802639,0.0003545671,0.00004656556,0.0002514096,0.0002991194,0.003096773,0.0005870888],"genre_scores_gemma":[0.1276241,0.0002385696,0.8690225,0.0002993166,0.00004876978,0.0002534452,0.001142449,0.0004718306,0.0008989134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01049036,"threshold_uncertainty_score":0.05547899,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4729249625945691,"score_gpt":0.5056587030425448,"score_spread":0.03273374044797572,"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."}}