{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001254109,0.0002004397,0.000308462,0.0008962842,0.001075617,0.0001045031,0.0002037408,0.00004117224,0.00001979143],"category_scores_gemma":[0.0001357398,0.0001818653,0.00004213002,0.00117524,0.0001049776,0.0001852238,0.0001569295,0.0005258152,0.000007113386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001620488,"about_ca_system_score_gemma":0.0002882717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008082247,"about_ca_topic_score_gemma":0.00003029045,"domain_scores_codex":[0.9974462,0.0002457277,0.0003076778,0.0003095774,0.001049803,0.0006409764],"domain_scores_gemma":[0.9980389,0.001179303,0.00006008304,0.0002277116,0.0001349873,0.00035897],"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":[0.0004290768,0.0001672407,0.04628696,0.001657221,0.0004984781,0.00001982759,0.00487424,0.9422446,0.000615357,0.0007378974,0.0004832089,0.001985926],"study_design_scores_gemma":[0.00145885,0.0004464173,0.002669133,0.00009264881,0.00005389494,0.000002422875,0.00284094,0.9877063,0.003842737,0.0001172793,0.0004748644,0.0002945185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4276521,0.000049038,0.5702791,0.00001667583,0.0000438354,0.001043197,0.0004386839,0.0001395751,0.0003378856],"genre_scores_gemma":[0.9829069,0.000006465961,0.01438944,0.00001001123,0.00001232275,0.002546651,0.00006758557,0.00004021774,0.00002040617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5558896,"threshold_uncertainty_score":0.8272883,"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."}}