{"id":"W2990184042","doi":"10.1200/jco.2019.37.31_suppl.102","title":"Integration of electronic patient-reported outcomes into clinical workflows within the Epic electronic medical record.","year":2019,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Economic and Financial Impacts of Cancer","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Workflow; Electronic medical record; Phone; EPIC; Medical record; Medical emergency; Internal medicine; Database; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.05229702,0.0005309623,0.0007115697,0.003365854,0.0004333429,0.003760149,0.001072791,0.0004643768,0.002667302],"category_scores_gemma":[0.09654881,0.000599076,0.0007646602,0.003189518,0.0003873517,0.00304168,0.002693151,0.0009143035,0.001314187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084345,"about_ca_system_score_gemma":0.002893283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002056509,"about_ca_topic_score_gemma":0.00282131,"domain_scores_codex":[0.961965,0.0253657,0.006219382,0.002186457,0.003778021,0.0004855062],"domain_scores_gemma":[0.8833998,0.06056242,0.01812807,0.02389675,0.01078081,0.003232149],"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":[0.00149405,0.0008481477,0.1816878,0.00126804,0.0003706325,0.0001547117,0.002675373,0.001571919,0.001846666,0.001199899,0.01477148,0.7921112],"study_design_scores_gemma":[0.001393972,0.004859912,0.8159487,0.002287083,0.001224717,0.000924802,0.003328447,0.04178525,0.0137683,0.004168527,0.1098468,0.0004635293],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6015524,0.00546734,0.2328732,0.01596574,0.001370031,0.02045912,0.04202512,0.0288837,0.0514034],"genre_scores_gemma":[0.6479131,0.001339524,0.3210201,0.00161627,0.0005464579,0.004734585,0.01900333,0.0006546919,0.00317194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05229702,"threshold_uncertainty_score":0.2765763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07037778295952211,"score_gpt":0.3940859737962316,"score_spread":0.3237081908367095,"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."}}