{"id":"W2084175453","doi":"10.1097/cin.0000000000000144","title":"Electronic Medical Record in the Simulation Hospital","year":2015,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Network for Business Sustainability","funders":"","keywords":"Documentation; Medical record; Preceptor; Likert scale; Electronic medical record; Medical education; Medicine; Hospital medicine; Electronic health record; Nursing; MEDLINE; Medical emergency; Psychology; Health care; Family medicine; Computer 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003726377,0.0003460856,0.000297727,0.0005091441,0.000832428,0.001310305,0.0007878323,0.0005399879,0.008861613],"category_scores_gemma":[0.01136507,0.0002466106,0.000389924,0.0003839816,0.0003532941,0.0008681936,0.001559428,0.0007453106,0.001783867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001736467,"about_ca_system_score_gemma":0.003300193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00191747,"about_ca_topic_score_gemma":0.004099166,"domain_scores_codex":[0.9968611,0.001861379,0.0002240175,0.0002135593,0.0004568543,0.0003831916],"domain_scores_gemma":[0.991626,0.001763472,0.0006547971,0.0008690965,0.001769216,0.003317354],"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":[0.01745202,0.03250834,0.3353054,0.0006773856,0.000194548,0.004053753,0.004771599,0.03102797,0.0134773,0.003216434,0.03257151,0.5247439],"study_design_scores_gemma":[0.003404164,0.1360987,0.4949684,0.001164881,0.0003134857,0.01476824,0.01474113,0.07924503,0.0692554,0.004852428,0.1802806,0.000907474],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797901,0.0002063675,0.003801872,0.001274357,0.0001802484,0.0006951784,0.0005020013,0.0002256746,0.01332432],"genre_scores_gemma":[0.9878395,0.0001817382,0.006465974,0.0003527448,0.0000459746,0.0002342658,0.00040759,0.00001432286,0.004458009],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008861613,"threshold_uncertainty_score":0.02964503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06402584140833413,"score_gpt":0.4433118249829036,"score_spread":0.3792859835745694,"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."}}