{"id":"W3163905180","doi":"10.1145/3411764.3445172","title":"Automating Clinical Documentation with Digital Scribes: Understanding the Impact on Physicians","year":2021,"lang":"en","type":"article","venue":"","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Workflow; Documentation; Computer science; Implementation; Popularity; Exploratory research; Conversation; Multimedia; World Wide Web; Data science; Software engineering; Psychology; Database","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":[0.01764861,0.0003559008,0.000236501,0.001244518,0.0024784,0.004702919,0.001158872,0.001418906,0.003037506],"category_scores_gemma":[0.08577576,0.0005072752,0.0004311239,0.0007388931,0.0023283,0.003096935,0.003112304,0.0009316662,0.0006092629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00241549,"about_ca_system_score_gemma":0.00237367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002871866,"about_ca_topic_score_gemma":0.005218009,"domain_scores_codex":[0.9790399,0.01602913,0.0008986599,0.000694668,0.002592602,0.000744965],"domain_scores_gemma":[0.8901332,0.09031636,0.009170525,0.003262314,0.005119605,0.001998062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.001052674,0.001289469,0.09423041,0.001519243,0.00007222942,0.001834525,0.5691705,0.002169109,0.01769457,0.003129811,0.004037875,0.3037996],"study_design_scores_gemma":[0.0004503941,0.00424224,0.2137915,0.002298001,0.0003028421,0.0035368,0.6639488,0.01554475,0.01900719,0.004292846,0.07227202,0.0003126569],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717876,0.0006261907,0.01602437,0.003815928,0.00003508619,0.0002489318,0.00005594435,0.000210543,0.00719532],"genre_scores_gemma":[0.9728801,0.0006938081,0.02431216,0.0005535265,0.00002841992,0.0001289105,0.00004250457,0.00003843551,0.001322111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01764861,"threshold_uncertainty_score":0.09333587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1651219891252978,"score_gpt":0.5321502281447215,"score_spread":0.3670282390194237,"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."}}