{"id":"W2418021896","doi":"10.1590/0004-282x20150127","title":"Stroke prevention and control in Brazil: missed opportunities","year":2015,"lang":"en","type":"letter","venue":"Arquivos de Neuro-Psiquiatria","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stroke (engine); Control (management); Medicine; Psychology; Computer science; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.004442009,0.0005134583,0.001469276,0.0009415932,0.002501656,0.003302377,0.001413558,0.01242912,0.004631204],"category_scores_gemma":[0.01846812,0.0003467209,0.0009392654,0.00088947,0.00169498,0.003322687,0.002175186,0.01144377,0.001162234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005018425,"about_ca_system_score_gemma":0.009255959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02084401,"about_ca_topic_score_gemma":0.0429254,"domain_scores_codex":[0.9963741,0.001203248,0.0006523044,0.000236866,0.0009320446,0.0006013673],"domain_scores_gemma":[0.990689,0.003079413,0.0009212084,0.000351394,0.002448395,0.002510503],"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":[0.0002018353,0.0004529824,0.01685536,0.003583405,0.0001209886,0.01749871,0.001763234,0.0003034407,0.001076194,0.01597822,0.5723536,0.369812],"study_design_scores_gemma":[0.0003710615,0.0004326918,0.02221482,0.0239357,0.0002381121,0.02832627,0.007894922,0.001854038,0.0004422647,0.03663192,0.8775173,0.0001408522],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.001230668,0.04016853,0.0001613259,0.9502321,0.005858068,0.00001542419,0.00004155883,0.00001639512,0.002275938],"genre_scores_gemma":[0.07851015,0.1973934,0.003023621,0.6240866,0.09218543,0.0001999882,0.0002297499,0.00003912822,0.004331955],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02084401,"threshold_uncertainty_score":0.04144537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08653739731695187,"score_gpt":0.3008734711112671,"score_spread":0.2143360737943152,"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."}}