{"id":"W2321962423","doi":"10.5430/jha.v5n3p98","title":"Role of Social Knowledge Networking technology in facilitating meaningful use of Electronic Health Record medication reconciliation","year":2016,"lang":"en","type":"article","venue":"Journal of Hospital Administration","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality","keywords":"Context (archaeology); Narrative; Knowledge management; Health care; Action (physics); Electronic health record; Meaningful use; Patient safety; Medicine; Psychology; Public relations; Medical education; Nursing; Business; Computer science; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.00898652,0.0002879622,0.0002137391,0.002302689,0.003575128,0.006428048,0.0009829383,0.001543855,0.004126564],"category_scores_gemma":[0.02308018,0.0002480453,0.0005028294,0.001599604,0.003914896,0.01182176,0.004719576,0.001807291,0.000327593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003228997,"about_ca_system_score_gemma":0.006998584,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002137975,"about_ca_topic_score_gemma":0.006666957,"domain_scores_codex":[0.9875275,0.01009473,0.0004349329,0.0003774325,0.001049433,0.000515925],"domain_scores_gemma":[0.9673081,0.02810214,0.002245038,0.0004847384,0.001252099,0.0006079759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001428486,0.0002686311,0.0122685,0.009487978,0.00009868795,0.002840564,0.3295858,0.0004360329,0.001041438,0.2264043,0.01118043,0.4062448],"study_design_scores_gemma":[0.00007348626,0.0003823631,0.01979092,0.02369967,0.0002515604,0.001920586,0.3527955,0.001944375,0.002267809,0.04212905,0.5546452,0.00009941295],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4072814,0.05640703,0.02321416,0.1033428,0.00138062,0.001364124,0.0003880665,0.0001134904,0.4065083],"genre_scores_gemma":[0.9531851,0.02619623,0.01047414,0.004256868,0.0002816472,0.0007026787,0.00008120485,0.00002651737,0.004795562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00898652,"threshold_uncertainty_score":0.04752582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03968695239985003,"score_gpt":0.3929970500279653,"score_spread":0.3533100976281152,"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."}}