{"id":"W3035916362","doi":"10.2196/19866","title":"The Role of Health Technology and Informatics in a Global Public Health Emergency: Practices and Implications From the COVID-19 Pandemic","year":2020,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":198,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Telemedicine; Health care; Medicine; Public health; Telehealth; Coronavirus disease 2019 (COVID-19); Middle East respiratory syndrome; Digital health; Global health; Health informatics; Medical emergency; Business; Disease; Economic growth; Nursing; Infectious disease (medical specialty)","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":[0.01883991,0.0004752337,0.0003100927,0.004071437,0.003387807,0.01361075,0.001488817,0.004030232,0.004814418],"category_scores_gemma":[0.03698462,0.0003307731,0.0004734177,0.00337732,0.01364865,0.01198043,0.007645361,0.005507884,0.0008565546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005589013,"about_ca_system_score_gemma":0.008749957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005208958,"about_ca_topic_score_gemma":0.005005843,"domain_scores_codex":[0.9820402,0.0133388,0.000646783,0.0006630443,0.002329392,0.0009817249],"domain_scores_gemma":[0.9530069,0.03205043,0.002605768,0.002719791,0.004538687,0.005078303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001325799,0.0004086518,0.0476601,0.002110163,0.00007536783,0.001875733,0.06321859,0.0008478621,0.0006542967,0.2296493,0.1028499,0.5505175],"study_design_scores_gemma":[0.00005858273,0.0003518677,0.03090556,0.01046204,0.00007919247,0.003189067,0.1853498,0.00172924,0.001034511,0.1391984,0.6275021,0.0001396687],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03172045,0.04018951,0.004370292,0.8232689,0.001729225,0.00007488844,0.00008230583,0.0001480542,0.09841634],"genre_scores_gemma":[0.7834429,0.1103338,0.01278602,0.08147167,0.004077162,0.0001622562,0.0001024051,0.0001484571,0.00747531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01883991,"threshold_uncertainty_score":0.09963614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.089719897220137,"score_gpt":0.4288465134815742,"score_spread":0.3391266162614371,"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."}}