{"id":"W4205161333","doi":"10.2196/preprints.28981","title":"Patient Perspectives on the Digitization of Personal Health Information in the Emergency Department: Mixed Methods Study During the COVID-19 Pandemic (Preprint)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC","keywords":"Digitization; Emergency department; Health care; Family medicine; Medicine; Coronavirus disease 2019 (COVID-19); Psychology; Nursing; Political science; Computer science; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.01405136,0.0003404483,0.0006226078,0.001290487,0.004265299,0.004103954,0.0009830883,0.001270482,0.002525331],"category_scores_gemma":[0.02483894,0.0008216818,0.0005675158,0.00198727,0.001710252,0.00284349,0.003020628,0.001592869,0.0003904099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004107467,"about_ca_system_score_gemma":0.005320597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03634499,"about_ca_topic_score_gemma":0.07218781,"domain_scores_codex":[0.9905883,0.006426505,0.0006203143,0.000524941,0.0007678489,0.001072081],"domain_scores_gemma":[0.9817929,0.01037293,0.003178214,0.0006636246,0.002461747,0.00153059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002306961,0.0004530182,0.1345772,0.0003779794,0.00004020238,0.0005352655,0.8478555,0.00002530358,0.0003140132,0.000203869,0.001674947,0.01371197],"study_design_scores_gemma":[0.00002326302,0.0004502256,0.06668698,0.0003130747,0.00002563378,0.0002462407,0.9286265,0.00008374915,0.0001564424,0.00006173885,0.003288952,0.00003723931],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997621,0.0002840169,0.0001556161,0.0007224226,0.00001564038,0.0001604608,0.000196005,0.000002524815,0.0008421935],"genre_scores_gemma":[0.9954038,0.0008226,0.0005790304,0.001579703,0.00003534757,0.0006484053,0.0001729538,0.00000794965,0.000750263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03634499,"threshold_uncertainty_score":0.07431161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08830056006560184,"score_gpt":0.4819500260312836,"score_spread":0.3936494659656817,"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."}}