{"id":"W4282943984","doi":"10.1097/01.hjh.0000837600.51239.74","title":"GEOGRAPHICAL ANALYSIS OF HYPERTENSION IN CANADIAN POPULATION","year":2022,"lang":"en","type":"article","venue":"Journal of Hypertension","topic":"Healthcare Systems and Public Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Medicine; Population; Demography; Quarter (Canadian coin); Population health; Environmental health; Health care; Community health; Ethnic group; Spatial analysis; Gerontology; Public health; Geography; Economic growth","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":[0.0009661645,0.0003659022,0.0003143235,0.006044115,0.001895734,0.001038683,0.0008498406,0.0002037506,0.003581739],"category_scores_gemma":[0.004315171,0.0001504302,0.001315982,0.01331295,0.0005101538,0.0002699897,0.0009513453,0.0003551263,0.0003206836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01316066,"about_ca_system_score_gemma":0.0263636,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.98757,"about_ca_topic_score_gemma":0.9835631,"domain_scores_codex":[0.99862,0.0001390039,0.000136235,0.0002008322,0.0006587824,0.0002451275],"domain_scores_gemma":[0.9978626,0.0001488837,0.0003342094,0.00008954631,0.001365561,0.0001991311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006244514,0.00001712069,0.9717923,0.0002922373,0.0001971236,0.0001575417,0.0008828312,0.001213936,0.0002405805,0.0009587701,0.007856443,0.01632862],"study_design_scores_gemma":[0.000003993967,0.00001164514,0.993999,0.00004895613,0.00005842392,0.00008167932,0.001011744,0.0008887718,0.0000620967,0.0001159295,0.003704484,0.00001331145],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8764426,0.003365945,0.002872589,0.001865625,0.0001111171,0.0004046781,0.0977817,0.0001875653,0.01696823],"genre_scores_gemma":[0.9779403,0.001192438,0.002961882,0.0001202066,0.00003047814,0.0001482959,0.01590179,0.00002010624,0.001684648],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01316066,"threshold_uncertainty_score":0.09548765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05279624483868178,"score_gpt":0.3026285390876794,"score_spread":0.2498322942489976,"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."}}