{"id":"W4403268486","doi":"10.2196/58035","title":"Digital Health Readiness: Making Digital Health Care More Inclusive","year":2024,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Digital health; mHealth; Health care; Computer science; Internet privacy; Psychology; Medicine; Nursing; Psychological intervention; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011267,0.0006893609,0.0004786895,0.004374604,0.003004788,0.009486847,0.001487872,0.001796718,0.006929352],"category_scores_gemma":[0.02606547,0.0004225838,0.0009226543,0.001500046,0.004103556,0.01271945,0.01782512,0.003420483,0.001376518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002544414,"about_ca_system_score_gemma":0.007979131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002664148,"about_ca_topic_score_gemma":0.004680118,"domain_scores_codex":[0.9922513,0.004445522,0.0004766395,0.0005949897,0.00144687,0.0007845704],"domain_scores_gemma":[0.9882217,0.00436065,0.001049271,0.001008633,0.001843704,0.003516043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008461442,0.0008517186,0.04117721,0.0008691917,0.00007974033,0.0003055655,0.03494031,0.0004933753,0.001364895,0.06824723,0.02358799,0.8279982],"study_design_scores_gemma":[0.0001150879,0.001244361,0.07822963,0.005700251,0.0002545708,0.001663785,0.1319532,0.002742437,0.00412713,0.1898823,0.5838104,0.0002768975],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2661638,0.006024431,0.1438264,0.2125497,0.002326897,0.002403542,0.0005503538,0.001966286,0.3641885],"genre_scores_gemma":[0.812003,0.005719199,0.1459932,0.01610484,0.0006356248,0.001272741,0.0004791742,0.0002225247,0.01756972],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.011267,"threshold_uncertainty_score":0.05958635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0479417978859531,"score_gpt":0.4794563407449691,"score_spread":0.431514542859016,"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."}}