{"id":"W4282002242","doi":"10.2196/37591","title":"Synchronous Teleconsultation and Monitoring Service Targeting COVID-19: Leveraging Insights for Postpandemic Health Care","year":2022,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Ministerio de Economía y Competitividad; Universidade Federal de Minas Gerais; Ministério da Educação; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Usability; Likert scale; System usability scale; Health care; Telemedicine; Coronavirus disease 2019 (COVID-19); Chatbot; Service (business); Pandemic; Nursing; Medicine; Medical education; Medical emergency; Psychology; World Wide Web; Business; Web usability; Computer science; Political 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":[0.0006413311,0.0001489164,0.0003194413,0.0001971707,0.0007528634,0.0000192046,0.00009458793,0.00006660527,0.0001242708],"category_scores_gemma":[0.0004536563,0.0001388045,0.00003289039,0.000313657,0.00003391941,0.0001704529,0.00009914544,0.000433453,0.000002566908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006862506,"about_ca_system_score_gemma":0.001876197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001923607,"about_ca_topic_score_gemma":0.0000225237,"domain_scores_codex":[0.9977775,0.00005965131,0.0009060613,0.0001399467,0.0007270275,0.0003898783],"domain_scores_gemma":[0.9982647,0.0003058707,0.0003492567,0.000126211,0.0001515202,0.0008024361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005027918,0.0001651001,0.04236354,0.01806398,0.0001305672,0.00003475188,0.5955927,0.0001365292,0.00008345213,0.0002863577,0.02456026,0.31808],"study_design_scores_gemma":[0.01717625,0.002889374,0.009953125,0.0004096104,0.0001143124,0.0006874987,0.5790468,0.0277754,0.0001367744,0.0001543468,0.3611513,0.0005052172],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973723,0.0014827,0.007159897,0.01478358,0.000379585,0.00214634,0.00003657788,0.0001843242,0.0001040309],"genre_scores_gemma":[0.9493557,0.0001605074,0.006737675,0.04201706,0.0003586741,0.0005046402,0.0008311847,0.00002259734,0.00001200257],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3365911,"threshold_uncertainty_score":0.5790493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03261710231403159,"score_gpt":0.3785908756534912,"score_spread":0.3459737733394596,"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."}}