{"id":"W2810419608","doi":"10.1177/2327857918071022","title":"Optimizing EMR User Experience: A Human Factors Approach to Hardware Assessment and Design for Inpatient and Emergency Units","year":2018,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Carleton University; Children's Hospital of Eastern Ontario","funders":"","keywords":"Workflow; Documentation; Context (archaeology); Computer science; Participatory design; Key (lock); Process management; Component (thermodynamics); User-centered design; Knowledge management; Engineering management; Operations management; Engineering; Database; Human–computer interaction; Computer security; Parallels","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":[],"consensus_categories":[],"category_scores_codex":[0.0007578679,0.0002723193,0.0004240612,0.0002079686,0.001240619,0.00004000579,0.0003673731,0.0001599217,0.00001149103],"category_scores_gemma":[0.0001055883,0.0002093799,0.00003950742,0.000150069,0.00008469761,0.0001734325,0.0002833101,0.0004113673,2.805742e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001326849,"about_ca_system_score_gemma":0.000271378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00139936,"about_ca_topic_score_gemma":0.0003841567,"domain_scores_codex":[0.9975401,0.00006801408,0.001032026,0.0005385357,0.0002701486,0.0005512351],"domain_scores_gemma":[0.9982086,0.0001731872,0.0006429514,0.0001285531,0.0005884381,0.0002582346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002149712,0.00008678602,0.8271323,0.001860208,0.00003989028,2.980859e-8,0.1499647,0.00004160375,0.001502509,0.01761767,0.001420713,0.0001186629],"study_design_scores_gemma":[0.004003653,0.005486759,0.7655325,0.003875646,0.0000405715,0.00000320233,0.1925274,0.002120702,0.00298405,0.0008121896,0.02133959,0.001273703],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948171,0.0001046457,0.0001034256,0.0005038711,0.000911428,0.002661165,0.0000725094,0.00002493954,0.000800924],"genre_scores_gemma":[0.9975922,0.0001250653,0.001071473,0.0003067989,0.0002251559,0.0004495324,0.00002189763,0.00004076089,0.0001671392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0615998,"threshold_uncertainty_score":0.9541967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1226748954194349,"score_gpt":0.4252865260215024,"score_spread":0.3026116306020675,"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."}}