{"id":"W4301759244","doi":"10.1007/978-3-031-01658-5_2","title":"The Electronic Medical Record (EMR): Design, Safety, and Meaningful Use","year":2014,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on biomedical engineering","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Government (linguistics); Business; Meaningful use; Medical record; Product (mathematics); Public relations; Patient safety; Medicine; Health care; Nursing; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.006106016,0.0009769516,0.001445251,0.0004572031,0.001244822,0.00006177615,0.0008932509,0.002697348,0.001161084],"category_scores_gemma":[0.01244145,0.0006644694,0.000245575,0.0001445015,0.0003182919,0.00005102084,0.000256984,0.006269034,0.0004122529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001494871,"about_ca_system_score_gemma":0.002156092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001266904,"about_ca_topic_score_gemma":0.0003482783,"domain_scores_codex":[0.9919035,0.0008552887,0.001902654,0.001029087,0.001825921,0.002483584],"domain_scores_gemma":[0.9658555,0.03127264,0.0005820735,0.0009963134,0.0001324298,0.001160995],"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":[0.001005071,0.00004713775,0.00002089907,0.002439941,0.001254599,0.0001191208,0.0004303058,0.0001031779,0.0001600205,0.3221661,0.05637728,0.6158763],"study_design_scores_gemma":[0.0004079736,0.0003979659,0.00002391777,0.003508843,0.00008878136,0.00004027146,0.000006636277,0.005022119,0.00001605379,0.001916843,0.9879311,0.0006394839],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0003665631,0.03776641,0.7209606,0.06008843,0.02041126,0.01563635,0.0002213816,0.004877776,0.1396713],"genre_scores_gemma":[0.1193862,0.1163027,0.003805222,0.01933012,0.03118401,0.004011607,0.0002796054,0.004627579,0.701073],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9315538,"threshold_uncertainty_score":0.999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805934480505689,"score_gpt":0.3087187579546543,"score_spread":0.2806594131495974,"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."}}