{"id":"W2554522310","doi":"10.1016/j.ccl.2016.08.010","title":"Innovative Approaches to Hypertension Control in Low- and Middle-Income Countries","year":2016,"lang":"en","type":"review","venue":"Cardiology Clinics","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto; Population Health Research Institute; University of Ottawa; Wilfrid Laurier University; Queen's University","funders":"National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research; National Institutes of Health; Canadian Stroke Network; Grand Challenges Canada; Ministry of Higher Education, Malaysia; Fogarty International Center; National Heart, Lung, and Blood Institute; International Development Research Centre","keywords":"Medicine; Low and middle income countries; Control (management); Developing country; Economic growth; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001852556,0.0009879007,0.002771876,0.003529989,0.0003662095,0.001778584,0.001228245,0.001144682,0.004554512],"category_scores_gemma":[0.002929224,0.000373961,0.001432104,0.004786505,0.0006087736,0.001553237,0.001084766,0.001597269,0.0003849908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009194026,"about_ca_system_score_gemma":0.002874206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003857861,"about_ca_topic_score_gemma":0.01103913,"domain_scores_codex":[0.999392,0.0001599224,0.000159393,0.00008090081,0.0001544945,0.00005316286],"domain_scores_gemma":[0.9983348,0.001147715,0.0002687395,0.00002449312,0.0001640272,0.00006031829],"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":[0.0002315436,0.0001575465,0.001035339,0.1655966,0.001667798,0.0002106673,0.0001691407,0.0002688547,0.0003457107,0.002876975,0.01075061,0.8166891],"study_design_scores_gemma":[0.0005487467,0.0006340693,0.01547331,0.2562562,0.01119761,0.001759057,0.001056263,0.00030514,0.0006135225,0.004768306,0.7072645,0.0001233563],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00007372485,0.9995752,0.0000176496,0.0001310691,0.00006075926,0.000002754012,0.000009377417,9.59213e-7,0.0001284898],"genre_scores_gemma":[0.0006727198,0.9990191,0.00008176734,0.0001245682,0.00006160115,0.000003849473,0.000009157198,2.488503e-7,0.00002700662],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004554512,"threshold_uncertainty_score":0.01523638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2113090493605244,"score_gpt":0.3487803374056087,"score_spread":0.1374712880450843,"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."}}