{"id":"W1999259627","doi":"10.4018/jhisi.2010110303","title":"A Framework for Data and Mined Knowledge Interoperability in Clinical Decision Support Systems","year":2010,"lang":"en","type":"article","venue":"International Journal of Healthcare Information Systems and Informatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Interoperability; Clinical decision support system; Computer science; Decision support system; Guideline; Health care; Knowledge management; Quality (philosophy); Data science; Data mining; Medicine; World Wide 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002682034,0.0001042409,0.0002656746,0.0001592449,0.00004058323,0.0001616587,0.0004201286,0.0002894581,0.000001259223],"category_scores_gemma":[0.002120628,0.0000779681,0.00004261274,0.00004616831,0.0001027459,0.0001228585,0.000209294,0.0003162923,0.000001848926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001770915,"about_ca_system_score_gemma":0.0002156669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004263389,"about_ca_topic_score_gemma":0.00004687647,"domain_scores_codex":[0.9976276,0.00004839937,0.001883805,0.00007687556,0.000233352,0.0001299262],"domain_scores_gemma":[0.9978701,0.0002348725,0.0007452392,0.0002380779,0.0007769538,0.0001346872],"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":[0.001093032,0.0001448109,0.0756987,0.001105254,0.0002047008,0.000003279169,0.005027028,0.00003268077,0.00007061499,0.008849451,0.00958887,0.8981816],"study_design_scores_gemma":[0.00263437,0.00120547,0.01204006,0.0006707044,0.00001567419,0.000806162,0.007732696,0.03720678,0.00002409756,0.0002813815,0.9371498,0.0002328352],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8699433,0.0009120715,0.1212528,0.0008540469,0.006272526,0.0003899782,0.000207104,0.000008478503,0.0001596647],"genre_scores_gemma":[0.9788433,0.0005299007,0.01979908,0.0002515131,0.0004266527,0.000007668001,0.0001291223,0.000004038182,0.000008782155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9275609,"threshold_uncertainty_score":0.3179447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05877489027119352,"score_gpt":0.4263281211931375,"score_spread":0.367553230921944,"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."}}