{"id":"W3047061091","doi":"10.2196/15076","title":"Evaluating Asthma Mobile Apps to Improve Asthma Self-Management: User Ratings and Sentiment Analysis of Publicly Available Apps","year":2020,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Minority Health and Health Disparities","keywords":"mHealth; Usability; Asthma; Sentiment analysis; App store; Mobile apps; Descriptive statistics; Medicine; Psychology; Computer science; World Wide Web; Artificial intelligence; Statistics; Psychiatry; Psychological intervention","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":[0.007805693,0.0004088012,0.0006598488,0.003408084,0.0003938706,0.001259486,0.0002509711,0.0003454842,0.0008142654],"category_scores_gemma":[0.03673489,0.0001804327,0.0006686858,0.001992204,0.000248591,0.001247325,0.0007354253,0.0003886588,0.0003743582],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004376885,"about_ca_system_score_gemma":0.0004538739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001391037,"about_ca_topic_score_gemma":0.003695428,"domain_scores_codex":[0.9938665,0.002498745,0.000910494,0.0004517654,0.002094594,0.0001778467],"domain_scores_gemma":[0.9468224,0.02852003,0.01023589,0.0007747599,0.01293281,0.0007142026],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001976398,0.0004562379,0.6780286,0.008856832,0.00085904,0.0006224622,0.01387213,0.0008877724,0.015527,0.0003183493,0.01614778,0.2624474],"study_design_scores_gemma":[0.00006167728,0.00141071,0.9552257,0.001562165,0.0006616146,0.0008723865,0.00650736,0.01081537,0.004583034,0.0002072977,0.01798032,0.0001123744],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9832059,0.00543879,0.002155455,0.0004599769,0.00009885318,0.0005152538,0.003118977,0.0001141938,0.004892718],"genre_scores_gemma":[0.9869856,0.002101025,0.006552429,0.0002176465,0.000138166,0.0005573288,0.002307629,0.00003757069,0.001102618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007805693,"threshold_uncertainty_score":0.04128093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06566732704793789,"score_gpt":0.4406845306896088,"score_spread":0.375017203641671,"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."}}