{"id":"W2032227143","doi":"10.4018/jissc.2010092905","title":"Managing Demographic Data Inconsistencies in Healthcare Information Systems","year":2010,"lang":"en","type":"article","venue":"International Journal of Information Systems and Social Change","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agfa-Gevaert (Canada); Athabasca University","funders":"","keywords":"Computer science; Workflow; XML; Disparate system; Information system; Data exchange; RDF; DICOM; Data science; Database; Health informatics; Information retrieval; Health care; Data mining; World Wide Web; Semantic Web","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":[0.07491395,0.0004871069,0.001359691,0.008000193,0.004110523,0.009166405,0.003906925,0.002290337,0.001849879],"category_scores_gemma":[0.1974196,0.00131355,0.0007983274,0.01138836,0.003007118,0.01687234,0.007932097,0.002344091,0.0004506875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004402112,"about_ca_system_score_gemma":0.007841553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005962736,"about_ca_topic_score_gemma":0.003281599,"domain_scores_codex":[0.9175269,0.03962696,0.01322357,0.00598988,0.02184609,0.001786588],"domain_scores_gemma":[0.8363639,0.09693948,0.02108387,0.0190531,0.02524526,0.001314394],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006198479,0.0003907961,0.1604288,0.0008699292,0.000381226,0.004108275,0.01874031,0.04152377,0.002665344,0.3908905,0.015451,0.3639302],"study_design_scores_gemma":[0.0002667165,0.0003690058,0.02581606,0.0017178,0.0008578413,0.006213229,0.02413288,0.2324867,0.03792361,0.4164619,0.2532862,0.0004679971],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2540239,0.003040797,0.7028724,0.01711323,0.0005601064,0.0008184659,0.003444529,0.002926484,0.01520009],"genre_scores_gemma":[0.6940809,0.001314423,0.2937744,0.001859037,0.0003127756,0.0004356541,0.00506966,0.000561393,0.002591879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07491395,"threshold_uncertainty_score":0.3961875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2057754293188543,"score_gpt":0.4051348497958837,"score_spread":0.1993594204770294,"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."}}