{"id":"W2760377918","doi":"10.1097/hjh.0000000000001524","title":"Electronic monitoring to diagnose and treat drug nonadherence","year":2017,"lang":"en","type":"letter","venue":"Journal of Hypertension","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Biostatistics; Epidemiology; University hospital; Family medicine; Health care; Library science; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002618819,0.0001952559,0.0003598165,0.001103669,0.0006941037,0.0007508379,0.000444879,0.002718465,0.007445165],"category_scores_gemma":[0.01516505,0.0001468835,0.0003033792,0.0008142208,0.0003225512,0.000853558,0.0005254303,0.003650844,0.002043493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007811271,"about_ca_system_score_gemma":0.001131854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002943471,"about_ca_topic_score_gemma":0.005457476,"domain_scores_codex":[0.9975986,0.001379161,0.0003060046,0.0001289517,0.0004231108,0.0001641707],"domain_scores_gemma":[0.9902864,0.005428811,0.001357223,0.0004991075,0.001490712,0.0009377545],"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":[0.0003445597,0.0004920787,0.1007839,0.0003443455,0.00007252484,0.00417401,0.0005576264,0.00008967665,0.0004949702,0.002873441,0.5777556,0.3120174],"study_design_scores_gemma":[0.0009333971,0.001237113,0.2465721,0.007494765,0.0001528412,0.01390804,0.002565171,0.001989015,0.001220662,0.01281639,0.7110013,0.0001092454],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.04153223,0.02592539,0.001452066,0.8198768,0.00964589,0.0003043993,0.0007589138,0.000111697,0.1003926],"genre_scores_gemma":[0.5161151,0.04055073,0.00521247,0.3778222,0.03787525,0.0006326641,0.0007942384,0.00004655468,0.02095073],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.007445165,"threshold_uncertainty_score":0.02490652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04955762697875235,"score_gpt":0.2876317961108996,"score_spread":0.2380741691321473,"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."}}