{"id":"W2937545591","doi":"10.2196/13257","title":"Apps to Support Self-Management for People With Hypertension: Content Analysis","year":2019,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Self-management; Content analysis; mHealth; Content (measure theory); Computer science; Psychology; Medicine; Nursing; Psychological intervention; Sociology; 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":[0.005106308,0.0004025247,0.0005979808,0.01264442,0.0005543161,0.001592981,0.0004755192,0.0003146179,0.001854353],"category_scores_gemma":[0.03152105,0.0002917987,0.001061148,0.0103523,0.0004197163,0.001972345,0.001748508,0.0004552575,0.0004495659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111649,"about_ca_system_score_gemma":0.001923517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003023908,"about_ca_topic_score_gemma":0.005770352,"domain_scores_codex":[0.9974328,0.0008267812,0.0005241933,0.0002635288,0.0008073185,0.0001453899],"domain_scores_gemma":[0.9678378,0.02284226,0.004007493,0.0005323404,0.004438548,0.0003415334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.000467196,0.0004560759,0.5074211,0.01897938,0.0005261954,0.0009350393,0.05524636,0.0006228556,0.004039611,0.00122786,0.01190021,0.3981781],"study_design_scores_gemma":[0.00005478726,0.0003303881,0.9339417,0.005267664,0.0008743023,0.0007241771,0.0233521,0.005994619,0.001654977,0.00094527,0.02675717,0.0001029332],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9643146,0.002596793,0.005494131,0.0006297866,0.00005089204,0.006299945,0.01545049,0.000202873,0.004960548],"genre_scores_gemma":[0.9318784,0.004137232,0.04181594,0.000216724,0.00009713649,0.007685035,0.01189877,0.00009012017,0.002180619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01264442,"threshold_uncertainty_score":0.02700508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08447099056713704,"score_gpt":0.420686056504077,"score_spread":0.3362150659369399,"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."}}