{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002699399,0.00007700381,0.0002375136,0.00002306204,0.00005948549,0.000008710846,0.00004140766,0.00004288241,0.005046146],"category_scores_gemma":[0.0008903647,0.00006594028,0.00002873709,0.0001936512,0.00004434822,0.00004258687,0.0000292373,0.0002007017,0.0003841016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001432928,"about_ca_system_score_gemma":0.0002426918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005258958,"about_ca_topic_score_gemma":0.000003469033,"domain_scores_codex":[0.9990947,0.00006472947,0.0002353124,0.0002165613,0.0002677483,0.0001209104],"domain_scores_gemma":[0.9993722,0.00006000873,0.00009757196,0.0001821609,0.0001339192,0.0001540918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001027787,0.0004570969,0.1040412,0.05706406,0.0001961021,0.0003613098,0.0007149142,5.11247e-7,0.0256359,0.001997231,0.1334255,0.6760035],"study_design_scores_gemma":[0.00532019,0.0005549671,0.0320551,0.3677388,0.0004918775,0.001141379,0.0005251188,0.001784156,0.008641404,0.0005689223,0.5804212,0.0007568376],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01737942,0.7576593,0.002724865,0.1311079,0.000596152,0.002577819,0.000003636679,0.0003899956,0.08756089],"genre_scores_gemma":[0.215966,0.5207792,0.006095607,0.02871037,0.0005279845,0.0007029492,0.000496661,0.00005639853,0.2266648],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6752466,"threshold_uncertainty_score":0.9958634,"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."}}