{"id":"W2394953419","doi":"10.2196/medinform.4553","title":"Putting Meaning into Meaningful Use: A Roadmap to Successful Integration of Evidence at the Point of Care","year":2016,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Documentation; Point of care; Health information technology; Clinical decision support system; Health care; Quality (philosophy); Evidence-based medicine; Consistency (knowledge bases); Usability; Health informatics; Knowledge management; Service (business); Medicine; Computer science; Decision support system; Nursing; Business; Data mining; Artificial intelligence; Public health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.3824472,0.004163604,0.007525798,0.02001276,0.009817694,0.04899377,0.01060152,0.03242013,0.01101842],"category_scores_gemma":[0.3263571,0.0046809,0.007873663,0.01306841,0.05942908,0.0935023,0.05328164,0.04585539,0.004611656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02227214,"about_ca_system_score_gemma":0.1463832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008064181,"about_ca_topic_score_gemma":0.007337563,"domain_scores_codex":[0.674525,0.2228208,0.04078826,0.01013138,0.0430296,0.00870498],"domain_scores_gemma":[0.3300331,0.5374321,0.01228089,0.03740432,0.0630148,0.01983479],"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":[0.0001977293,0.0004856831,0.00312902,0.02504912,0.0005768648,0.0007977571,0.01898891,0.001635405,0.001040503,0.371633,0.03589506,0.540571],"study_design_scores_gemma":[0.0001745595,0.0004529901,0.003129759,0.06985006,0.0004189854,0.0009787405,0.02021312,0.002002392,0.0009876942,0.6638676,0.2374947,0.0004293795],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002759929,0.1171083,0.1353802,0.7178329,0.005148156,0.002097448,0.00018434,0.0007317531,0.01875697],"genre_scores_gemma":[0.07120935,0.1096012,0.7441422,0.06492355,0.003587988,0.004021988,0.0003477608,0.000486632,0.001679515],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3824472,"threshold_uncertainty_score":0.7615526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1032951402056048,"score_gpt":0.4597458749476288,"score_spread":0.356450734742024,"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."}}