{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01111165,0.0007209971,0.0007555975,0.005956496,0.00127493,0.005286574,0.001314876,0.001687727,0.002051518],"category_scores_gemma":[0.03165942,0.0004065279,0.001053161,0.003578495,0.005981252,0.01186596,0.002159508,0.001896088,0.000271494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003336974,"about_ca_system_score_gemma":0.001141682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003113639,"about_ca_topic_score_gemma":0.00107465,"domain_scores_codex":[0.989845,0.002958987,0.0009557901,0.001182537,0.004457478,0.0006001488],"domain_scores_gemma":[0.9686041,0.01922645,0.004664468,0.002325361,0.004178246,0.001001238],"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":[0.0001549722,0.0001063467,0.006066084,0.0003392058,0.00009537675,0.0001815584,0.001172813,0.04415937,0.004249033,0.873812,0.0009107325,0.06875247],"study_design_scores_gemma":[0.00005061546,0.0002558305,0.003642872,0.0002797394,0.00009115137,0.0003070061,0.0007909341,0.2789725,0.006307276,0.7009271,0.008239032,0.0001358391],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06102988,0.00157855,0.9212254,0.002096802,0.00005231223,0.00009645899,0.000139828,0.0001616727,0.01361913],"genre_scores_gemma":[0.7923023,0.0008976987,0.2048083,0.0002719948,0.0001667861,0.000127527,0.0001510081,0.00004096419,0.001233492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01111165,"threshold_uncertainty_score":0.05876482,"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."}}