{"id":"W4282946877","doi":"10.2196/35717","title":"A Scalable Risk-Scoring System Based on Consumer-Grade Wearables for Inpatients With COVID-19: Statistical Analysis and Model Development","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hasler Stiftung","keywords":"Medicine; Receiver operating characteristic; Wearable computer; Early warning score; Emergency medicine; Triage; Framingham Risk Score; Risk assessment; Physical therapy; Medical emergency; Internal medicine; Computer science","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":[0.003817741,0.001138962,0.00114147,0.001293856,0.0002934243,0.0009206232,0.001133596,0.0007757712,0.002525099],"category_scores_gemma":[0.009071354,0.0004101713,0.001364282,0.0007715762,0.0002745586,0.0006504494,0.001177481,0.001195586,0.0008185777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009455272,"about_ca_system_score_gemma":0.001464332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090255,"about_ca_topic_score_gemma":0.008354115,"domain_scores_codex":[0.9988856,0.0004684931,0.0001125717,0.000264962,0.0001980532,0.0000703948],"domain_scores_gemma":[0.9965414,0.002046518,0.0003935294,0.0002214236,0.0006599336,0.0001371057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006874167,0.0006202131,0.06261466,0.0002242379,0.0004675836,0.0003877398,0.0001399494,0.6539222,0.004463573,0.002567393,0.005995884,0.2679091],"study_design_scores_gemma":[0.00001420023,0.00006709306,0.003029373,0.000008715492,0.00001633874,0.0000330389,0.00001101509,0.9954333,0.0002997186,0.0008801694,0.0001954178,0.00001152836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0879601,0.0001822419,0.906086,0.0004321597,0.00005869745,0.0004482912,0.001213538,0.003131435,0.0004875498],"genre_scores_gemma":[0.6202832,0.0002862506,0.373056,0.0002066331,0.0001055065,0.001371635,0.003464853,0.0001465821,0.00107939],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01090255,"threshold_uncertainty_score":0.02167821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04696327933109826,"score_gpt":0.3418708023036551,"score_spread":0.2949075229725568,"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."}}