{"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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0224138,0.00007716111,0.0002424564,0.0001301955,0.0005119851,0.002336628,0.004255051,0.0000297141,0.00007370351],"category_scores_gemma":[0.007031674,0.00004731866,0.00001962944,0.00006203949,0.0001017584,0.05900216,0.002837756,0.0001419841,0.0000517918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001093236,"about_ca_system_score_gemma":0.00008152003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001347682,"about_ca_topic_score_gemma":0.00008555132,"domain_scores_codex":[0.997152,0.0001453698,0.001225993,0.000165596,0.001190182,0.0001208469],"domain_scores_gemma":[0.9931403,0.0003544428,0.002416975,0.003678926,0.0003096001,0.00009972096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003396439,0.00007231635,0.02509123,0.0001297332,0.0001392491,0.00001448056,0.00146423,0.00002544168,0.00001083491,0.01956325,0.1666232,0.7865264],"study_design_scores_gemma":[0.0007154831,0.00005744772,0.08131846,0.00006412008,0.00002873213,0.00004750738,0.00331194,0.003230717,0.00001799727,0.003151797,0.9079359,0.0001199174],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5177891,0.0002965221,0.4129988,0.01693341,0.001126611,0.0004138806,0.007338042,0.00004741095,0.04305623],"genre_scores_gemma":[0.9530135,0.0003379172,0.04388603,0.001262162,0.0002357761,6.395828e-7,0.0009921059,0.000005440054,0.0002664046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7864065,"threshold_uncertainty_score":0.9986991,"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."}}