{"id":"W3199180167","doi":"10.2196/26993","title":"Machine Learning and Medication Adherence: Scoping Review","year":2021,"lang":"en","type":"article","venue":"JMIRx Med","topic":"Medication Adherence and Compliance","field":"Medicine","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. National Library of Medicine","keywords":"Random forest; Machine learning; Scopus; Logistic regression; Support vector machine; Categorization; Artificial intelligence; Protocol (science); MEDLINE; Systematic review; Pharmacy; Computer science; Medicine; Alternative medicine; Family medicine","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":[0.02092195,0.002076646,0.006192153,0.01894153,0.001502389,0.006066371,0.002702794,0.004482883,0.00800098],"category_scores_gemma":[0.108556,0.001311362,0.006604062,0.01682203,0.001712234,0.004742197,0.003094035,0.003078426,0.00112741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004881043,"about_ca_system_score_gemma":0.02480438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006172094,"about_ca_topic_score_gemma":0.009259568,"domain_scores_codex":[0.9827998,0.006366176,0.005836138,0.0009334187,0.003551957,0.0005125066],"domain_scores_gemma":[0.9030198,0.0788824,0.008165723,0.001433627,0.007994171,0.0005042063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.000102428,0.0000417981,0.0005760527,0.7618716,0.001713636,0.0001442035,0.0005633367,0.0004219012,0.000160399,0.002304452,0.01029602,0.2218043],"study_design_scores_gemma":[0.00002537956,0.00005063208,0.000564918,0.9485889,0.003735675,0.0001963788,0.0002364775,0.0001320969,0.00009600945,0.001285749,0.04506705,0.00002072587],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002228094,0.9965946,0.0005111697,0.001114811,0.0003598925,0.0002562342,0.0001750947,0.00001406391,0.0007512674],"genre_scores_gemma":[0.002615156,0.9950315,0.0008444371,0.0004756246,0.0002352636,0.0004984252,0.0001636089,0.000007635105,0.0001283858],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.02092195,"threshold_uncertainty_score":0.1106472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05729443254300634,"score_gpt":0.3936963916980865,"score_spread":0.3364019591550802,"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."}}