{"id":"W2995770770","doi":"10.2196/18859","title":"Correction: Using Goal-Directed Design to Create a Mobile Health App to Improve Patient Compliance With Hypertension Self-Management: Development and Deployment","year":2020,"lang":"en","type":"erratum","venue":"JMIR mhealth and uhealth","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software deployment; mHealth; Mobile apps; Self-management; Goal setting; Computer science; Compliance (psychology); eHealth; Medicine; Process management; Psychology; Psychological intervention; World Wide Web; Health care; Nursing; Engineering; Artificial intelligence; Software engineering","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":[0.008266882,0.003158504,0.002034434,0.003401764,0.004130395,0.005048395,0.004363969,0.01217861,0.06169685],"category_scores_gemma":[0.1294971,0.001388229,0.002226394,0.002382764,0.004057333,0.003064017,0.003144931,0.01737671,0.03400705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005568468,"about_ca_system_score_gemma":0.01149835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03346299,"about_ca_topic_score_gemma":0.03709342,"domain_scores_codex":[0.9880568,0.001931618,0.002189186,0.001338687,0.005740332,0.0007434307],"domain_scores_gemma":[0.9287269,0.02123824,0.003241428,0.002894245,0.04167552,0.002223652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002925579,0.000007788107,0.00004436791,0.0001397158,0.000008968537,0.0001910975,0.00006642125,0.00003754122,0.00003265621,0.000775127,0.9929942,0.005672819],"study_design_scores_gemma":[0.00007128794,0.00003728169,0.0003838205,0.0008117975,0.00003664623,0.0006036499,0.00018713,0.0003972226,0.0002952645,0.001556995,0.9955591,0.0000598306],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.000117879,0.0006887695,0.001373894,0.08005036,0.9135221,0.00004777681,0.00112959,0.0006989869,0.002370671],"genre_scores_gemma":[0.01493944,0.01250485,0.01468846,0.2557049,0.4186579,0.0008552565,0.003178678,0.003328027,0.2761424],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06169685,"threshold_uncertainty_score":0.2063965,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08106252924914516,"score_gpt":0.3931814168163764,"score_spread":0.3121188875672312,"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."}}