{"id":"W2895821558","doi":"10.2196/11919","title":"Mobile Phone Apps Targeting Medication Adherence: Quality Assessment and Content Analysis of User Reviews","year":2018,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":120,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Canada; Centre for Advancing Health Outcomes; University of British Columbia","funders":"Canadian Arthritis Network; Michael Smith Health Research BC; Arthritis Society","keywords":"Mobile phone; mHealth; Medication adherence; Quality (philosophy); Internet privacy; Computer science; Multimedia; World Wide Web; Medicine; Psychological intervention; Nursing; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1417627,0.0007564616,0.002308669,0.02306929,0.001294626,0.003050531,0.001466503,0.0007255636,0.0006965489],"category_scores_gemma":[0.3573693,0.000734861,0.002364916,0.01797159,0.001387669,0.003264856,0.003568782,0.0006735781,0.0002167043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004890446,"about_ca_system_score_gemma":0.006728749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003588924,"about_ca_topic_score_gemma":0.005600975,"domain_scores_codex":[0.8054545,0.119977,0.03705548,0.004645414,0.03106698,0.001800528],"domain_scores_gemma":[0.5091436,0.3220498,0.05574753,0.01241532,0.09924763,0.001396031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.001496716,0.0004302673,0.3297823,0.04530849,0.002010379,0.0006552333,0.1796007,0.001234103,0.00645667,0.001361436,0.005949885,0.4257138],"study_design_scores_gemma":[0.000478968,0.003317015,0.7959,0.03536436,0.004517015,0.001693488,0.08887488,0.01167426,0.0104285,0.00199963,0.04519248,0.0005593309],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9071277,0.01703941,0.03588897,0.001687659,0.0001853364,0.02541981,0.006554255,0.0004911811,0.005605668],"genre_scores_gemma":[0.8745771,0.006775599,0.08133876,0.000481412,0.0001051686,0.03281187,0.003011931,0.0001413474,0.0007567829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1417627,"threshold_uncertainty_score":0.7497215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2490215490765998,"score_gpt":0.5559365724062096,"score_spread":0.3069150233296098,"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."}}