{"id":"W3111160883","doi":"10.2196/23190","title":"Mobile App–Based Remote Patient Monitoring in Acute Medical Conditions: Prospective Feasibility Study Exploring Digital Health Solutions on Clinical Workload During the COVID Crisis","year":2020,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workload; Context (archaeology); Telemedicine; Medicine; Digital health; Prospective cohort study; Medical emergency; Cohort; Telehealth; mHealth; Pandemic; Cohort study; Emergency medicine; Coronavirus disease 2019 (COVID-19); Health care; Computer science; Nursing; Internal medicine; Disease","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00407334,0.0004946376,0.0003774822,0.0008877863,0.0009200774,0.0009629618,0.0004525731,0.0007503387,0.002558722],"category_scores_gemma":[0.008097969,0.0004275483,0.0006247762,0.000422774,0.0006906981,0.001240574,0.001342649,0.0009106997,0.0005634229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005860631,"about_ca_system_score_gemma":0.001338404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001537974,"about_ca_topic_score_gemma":0.00184287,"domain_scores_codex":[0.9970188,0.0016193,0.0002214919,0.0002782288,0.0003578615,0.0005042918],"domain_scores_gemma":[0.9939252,0.002084779,0.001674831,0.0002536247,0.0009565738,0.001105171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02133154,0.09136975,0.8188151,0.0007867339,0.0001952502,0.001373776,0.01066031,0.0005788021,0.007231808,0.0002506728,0.0009994614,0.04640684],"study_design_scores_gemma":[0.001311981,0.2083396,0.7741705,0.0001323959,0.0001382925,0.0004908789,0.0109852,0.001365171,0.001480455,0.0000785377,0.001413501,0.00009347775],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985043,0.00002602541,0.00009275235,0.00002949825,0.000005192935,0.001018241,0.0000563192,0.000002705436,0.0002649314],"genre_scores_gemma":[0.9969441,0.00007297019,0.0007335621,0.00009777107,0.00002249138,0.001823579,0.00008728867,0.000002433683,0.0002158014],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00407334,"threshold_uncertainty_score":0.02154213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3172637491666708,"score_gpt":0.5513446127790191,"score_spread":0.2340808636123483,"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."}}