{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003999224,0.0006940068,0.0004290033,0.0007022738,0.0003875784,0.0008223593,0.0009796129,0.0009722632,0.003717058],"category_scores_gemma":[0.00655299,0.0003357218,0.0007957132,0.0001556433,0.0003856586,0.001055254,0.001108366,0.0007250676,0.0007144531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003714005,"about_ca_system_score_gemma":0.001717842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305353,"about_ca_topic_score_gemma":0.001713586,"domain_scores_codex":[0.9983472,0.0007940929,0.0001378473,0.0001293545,0.0003695288,0.0002220543],"domain_scores_gemma":[0.9966348,0.001789912,0.0002118268,0.0001115005,0.0008269774,0.0004249755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01637263,0.08624675,0.1313916,0.01205883,0.0006661197,0.005031155,0.01087522,0.002929527,0.06477425,0.002017371,0.02047393,0.6471626],"study_design_scores_gemma":[0.01232226,0.3890439,0.3500808,0.004976502,0.002990214,0.008832786,0.02035066,0.04190496,0.07898302,0.001834773,0.08773962,0.0009404743],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9504196,0.0004820229,0.01274227,0.0006663149,0.0001187218,0.03033301,0.001024692,0.0005221916,0.003691142],"genre_scores_gemma":[0.8133338,0.001391,0.1466093,0.0013168,0.00008172633,0.03035911,0.00165095,0.00007427427,0.005182997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003999224,"threshold_uncertainty_score":0.02115011,"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."}}