{"id":"W3173012556","doi":"10.2196/27521","title":"An Early Warning Mobile Health Screening and Risk Scoring App for Preventing In-Hospital Transmission of COVID-19 by Health Care Workers: Development and Feasibility Study","year":2021,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Medicine; Transmission (telecommunications); Medical emergency; Warning system; Early warning system; Population; Coronavirus disease 2019 (COVID-19); Environmental health; Disease; Computer science; Infectious disease (medical specialty); Pathology","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":[0.003829187,0.0001348827,0.0003892798,0.0002519893,0.000687692,0.00005349159,0.00006005759,0.00005260887,0.000002236649],"category_scores_gemma":[0.0004211946,0.0001251755,0.00003514381,0.0005341884,0.0000764935,0.0002677495,0.00008701165,0.0005574637,2.141307e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004445419,"about_ca_system_score_gemma":0.000934444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008747748,"about_ca_topic_score_gemma":0.0001963859,"domain_scores_codex":[0.9973605,0.0006928369,0.0005647263,0.0004122552,0.0004879572,0.0004817705],"domain_scores_gemma":[0.9986344,0.0004333631,0.0002019143,0.0001670575,0.0002745422,0.0002887509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002633621,0.0006031362,0.5016336,0.001990487,0.00003518304,0.000004430631,0.2169422,0.000006303645,0.0009545995,9.607999e-7,0.00001875053,0.2775469],"study_design_scores_gemma":[0.009619364,0.01478342,0.4040969,0.002346137,0.00001330922,0.00001801073,0.5384151,0.003034302,0.02627525,0.00002330154,0.001074574,0.0003002804],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874424,0.002265329,0.006660353,0.00009987992,0.00001808652,0.003445314,0.00001176887,0.00004187411,0.00001504684],"genre_scores_gemma":[0.9925652,0.00004139456,0.006882573,0.00003575426,0.0000160373,0.0004128277,0.00001966892,0.00001856955,0.000007980406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.321473,"threshold_uncertainty_score":0.528924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001488365456966,"score_gpt":0.4775689108128444,"score_spread":0.3774200742671478,"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."}}