{"id":"W2903837644","doi":"10.2196/mhealth.9869","title":"Development and Evaluation of a Mobile Decision Support System for Hypertension Management in the Primary Care Setting in Brazil: Mixed-Methods Field Study on Usability, Feasibility, and Utility","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Financiadora de Estudos e Projetos; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Usability; Decision support system; Primary care; Medicine; mHealth; Computer science; Process management; Nursing; Psychological intervention; Human–computer interaction; Engineering; Family medicine; Data mining","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":[0.02266904,0.0002516658,0.0006269978,0.0003021893,0.001103468,0.0000122819,0.0001672943,0.0002308302,0.000007436375],"category_scores_gemma":[0.0002780863,0.0001913106,0.00002743437,0.0004086675,0.00009954533,0.00008136002,0.0001929624,0.0005086282,0.000002327933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007718633,"about_ca_system_score_gemma":0.001409813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004124523,"about_ca_topic_score_gemma":0.003316477,"domain_scores_codex":[0.9932581,0.002609234,0.001874189,0.0008782371,0.0005880017,0.0007923088],"domain_scores_gemma":[0.9956967,0.00237888,0.0005063624,0.0006516122,0.0003938616,0.0003725828],"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":[0.0006883708,0.0005225454,0.1788345,0.01359507,0.000004270983,7.449987e-7,0.01740069,7.658961e-7,0.000002700633,0.0003127559,0.0003220035,0.7883156],"study_design_scores_gemma":[0.00467261,0.001426637,0.9314494,0.000599654,0.00004932785,0.000003844473,0.057508,0.0007583451,0.000006332788,0.0003498185,0.003047041,0.0001289679],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97106,0.0009327027,0.0003282978,0.0005790523,0.0002856719,0.0260242,0.00002609281,0.00003249454,0.0007314358],"genre_scores_gemma":[0.9712202,0.0002664374,0.01207912,0.001933763,0.00008156089,0.01435414,0.00004100494,0.00001940098,0.000004359893],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7881867,"threshold_uncertainty_score":0.8487093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1646243399857358,"score_gpt":0.5403570949514497,"score_spread":0.3757327549657139,"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."}}