{"id":"W4205810258","doi":"10.2196/preprints.19514","title":"Monitoring and Management of Home-Quarantined Patients With COVID-19 Using a WeChat-Based Telemedicine System: Retrospective Cohort Study (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Telemedicine; Coronavirus disease 2019 (COVID-19); Medicine; Retrospective cohort study; Workforce; Medical emergency; Multidisciplinary approach; Economic shortage; Emergency medicine; Disease; Health care; Internal medicine; Infectious disease (medical specialty)","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":[0.0007893788,0.0003413116,0.0003884129,0.0008058648,0.0007340704,0.0006668863,0.0003730847,0.0006254215,0.001657004],"category_scores_gemma":[0.00193673,0.0005012445,0.0008451435,0.0009981893,0.0003290144,0.0008332065,0.0005552544,0.0006239016,0.0003843532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007071283,"about_ca_system_score_gemma":0.0006711719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01000706,"about_ca_topic_score_gemma":0.009474604,"domain_scores_codex":[0.9992329,0.0001589739,0.0001176537,0.0002329098,0.0001278662,0.0001297892],"domain_scores_gemma":[0.998676,0.0002204804,0.0005148549,0.00015874,0.0002438178,0.0001860136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001287252,0.0001062028,0.9983968,0.00001969728,0.00003372461,0.0001100886,0.0002116531,0.00001562156,0.000124465,0.000006783673,0.0001188708,0.0007272771],"study_design_scores_gemma":[0.00003078618,0.001000896,0.9966328,0.00002860246,0.00006790645,0.0003974497,0.001183484,0.0002028443,0.0001150132,0.00001022205,0.000316337,0.00001366236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991773,0.00008540564,0.00009737849,0.00001684824,0.000004154849,0.00006208133,0.0003854521,0.000002965129,0.000168359],"genre_scores_gemma":[0.9986773,0.0001395306,0.0001968213,0.00007736928,0.00001477884,0.0001097602,0.0006112105,0.000003985762,0.0001692763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01000706,"threshold_uncertainty_score":0.01989764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05608290448028447,"score_gpt":0.3680107433073536,"score_spread":0.3119278388270691,"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."}}