{"id":"W2941307870","doi":"10.2196/12982","title":"An Adaptive Mobile Health System to Support Self-Management for Persons With Chronic Conditions and Disabilities: Usability and Feasibility Studies","year":2019,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Disability, Independent Living, and Rehabilitation Research; National Center for Chronic Disease Prevention and Health Promotion; National Institutes of Health","keywords":"mHealth; Self-management; Personalization; Usability; Computer science; Health management system; Scalability; Process management; Knowledge management; Medicine; Human–computer interaction; Nursing; World Wide Web; Engineering; Psychological intervention; Artificial intelligence","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":[0.009295599,0.0005836972,0.0004719711,0.000856382,0.0004751803,0.0006870502,0.0007215013,0.0007529804,0.002178693],"category_scores_gemma":[0.01378759,0.0002687105,0.0008796758,0.0002986333,0.0004663419,0.001265108,0.001017391,0.0004561785,0.0002918894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004761288,"about_ca_system_score_gemma":0.0008943114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001336673,"about_ca_topic_score_gemma":0.001970172,"domain_scores_codex":[0.9973901,0.001598159,0.0002812917,0.0001865576,0.000363677,0.0001801986],"domain_scores_gemma":[0.9923821,0.005495126,0.0002631742,0.0003192042,0.001230135,0.0003102124],"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":[0.009950873,0.03866061,0.1361192,0.01172084,0.0007601521,0.001955447,0.02619918,0.004165963,0.04987959,0.001339335,0.006910454,0.7123384],"study_design_scores_gemma":[0.008916211,0.2716904,0.5438653,0.003683652,0.003013564,0.004495662,0.02553023,0.05448752,0.04271073,0.001569508,0.03926699,0.0007703466],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9872131,0.0002824944,0.005652074,0.0001447882,0.00003143038,0.005128582,0.0001786543,0.0001539916,0.001214929],"genre_scores_gemma":[0.9319569,0.0007195325,0.05762673,0.0002661372,0.00003930626,0.007681373,0.0004141524,0.00004876977,0.00124695],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009295599,"threshold_uncertainty_score":0.04916042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1441010273236641,"score_gpt":0.5491223858945126,"score_spread":0.4050213585708485,"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."}}