{"id":"W3216044589","doi":"10.2196/28981","title":"Patient Perspectives on the Digitization of Personal Health Information in the Emergency Department: Mixed Methods Study During the COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC","keywords":"Digitization; Emergency department; Medical emergency; Personal protective equipment; Pandemic; Coronavirus disease 2019 (COVID-19); Medicine; Telemedicine; Health care; 2019-20 coronavirus outbreak; Emergency medicine; Nursing; Computer science; Pathology; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.01113362,0.0003252293,0.000648942,0.001209457,0.004241319,0.003438003,0.001009453,0.001284844,0.001913552],"category_scores_gemma":[0.02031557,0.0007306621,0.0005199582,0.001836845,0.001736163,0.002095432,0.002926974,0.00166683,0.0002576072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00511973,"about_ca_system_score_gemma":0.006182618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07264344,"about_ca_topic_score_gemma":0.1382276,"domain_scores_codex":[0.9917731,0.005355885,0.0004793326,0.0004450188,0.0007310866,0.001215658],"domain_scores_gemma":[0.9857261,0.007281879,0.002459288,0.0005790845,0.002410836,0.001542882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003380877,0.0005268407,0.2068627,0.0003438712,0.00005255658,0.0008776145,0.7733258,0.0000369187,0.0003992887,0.0002310909,0.001602542,0.01540262],"study_design_scores_gemma":[0.00002355851,0.0004629929,0.1013733,0.0003180557,0.00002727575,0.0003866846,0.8936812,0.0001202634,0.0001505092,0.00005882344,0.003352894,0.00004456308],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982205,0.0002482835,0.0001158097,0.0004816017,0.000009792589,0.0001317653,0.0001351848,0.000001846461,0.0006553591],"genre_scores_gemma":[0.997,0.0005841705,0.0003695123,0.001091959,0.00001988862,0.000333474,0.0001167128,0.000005980818,0.0004782269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07264344,"threshold_uncertainty_score":0.1444412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07591471398235553,"score_gpt":0.4901926406546729,"score_spread":0.4142779266723174,"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."}}