{"id":"W1852537914","doi":"10.1109/nafips.1999.781771","title":"A characterization of information quality using fuzzy logic","year":2003,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"","keywords":"Fuzzy logic; Computer science; Information quality; Quality (philosophy); Perspective (graphical); Information system; Fuzzy set; Characterization (materials science); Data mining; Artificial intelligence; Engineering","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":[0.004291912,0.00004388728,0.0001154809,0.0001367929,0.0000438546,0.0001079178,0.0001916057,0.00002572893,0.0005874976],"category_scores_gemma":[0.001755692,0.00003136968,0.00003307596,0.0004282623,0.00002779608,0.001452975,0.00005266869,0.00002177308,0.0001841493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001259352,"about_ca_system_score_gemma":0.00002260945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005255717,"about_ca_topic_score_gemma":0.000008308671,"domain_scores_codex":[0.9983656,0.0002389482,0.0006294858,0.00009389131,0.0005942472,0.00007784034],"domain_scores_gemma":[0.9990682,0.0001014431,0.0003187208,0.0003159695,0.0001697518,0.00002592076],"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":[0.000007801947,0.00003575513,0.0009612002,0.0000120915,0.00000456062,8.113959e-8,0.0004041196,0.00004279259,0.0101455,0.9727302,0.0002222193,0.01543373],"study_design_scores_gemma":[0.001033542,0.00009942393,0.1162696,0.00002062366,0.00002408383,0.000003468932,0.007677073,0.002851175,0.03489538,0.4406675,0.3959914,0.0004667736],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4276488,0.000001232407,0.5158227,0.000164507,0.0001504553,0.0001203599,0.00002320071,0.00001554501,0.05605323],"genre_scores_gemma":[0.9924945,0.000002966436,0.005912977,0.0009496057,0.000006132415,0.000001543127,0.00003730823,0.000001136945,0.0005938396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5648457,"threshold_uncertainty_score":0.6432686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3191743449327472,"score_gpt":0.4482363332724146,"score_spread":0.1290619883396674,"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."}}