{"id":"W59605781","doi":"","title":"The Next Generation EMR.","year":2015,"lang":"en","type":"article","venue":"PubMed","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Health informatics; Informatics; eHealth; Meaningful use; Early adopter; Guideline; Computer science; Architecture; Knowledge management; Personalized medicine; Health records; Health care; Data science; Business; Internet privacy; Medicine; Engineering; Political science","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":[0.007498055,0.0003192648,0.0002468755,0.001362285,0.001170496,0.004941965,0.001668298,0.003300234,0.03057391],"category_scores_gemma":[0.01162271,0.0003505878,0.0006796456,0.001086359,0.001177969,0.009907774,0.004156919,0.001893033,0.01246938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002007024,"about_ca_system_score_gemma":0.00438629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002298297,"about_ca_topic_score_gemma":0.003351666,"domain_scores_codex":[0.9957,0.001710437,0.0003992843,0.000465489,0.001391619,0.0003331465],"domain_scores_gemma":[0.9920162,0.00172683,0.0007162645,0.001665411,0.002376647,0.001498626],"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":[0.00006009119,0.00007852077,0.005091469,0.0004273836,0.00003062976,0.0003323595,0.000992385,0.0002933496,0.001596385,0.1619633,0.2584207,0.5707135],"study_design_scores_gemma":[0.000008929633,0.00004351882,0.001937671,0.0002907843,0.000014736,0.0007488214,0.0004740226,0.000682689,0.0006770139,0.01584624,0.9792588,0.00001666499],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01896644,0.04446769,0.1676309,0.3450963,0.01043646,0.0005834466,0.002936833,0.008833214,0.4010487],"genre_scores_gemma":[0.2018246,0.04911161,0.3413556,0.09170925,0.006584245,0.0005700307,0.006124632,0.001003371,0.3017167],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.03057391,"threshold_uncertainty_score":0.1022799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4588186572161079,"score_gpt":0.4392237861042937,"score_spread":0.01959487111181424,"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."}}