{"id":"W2604143625","doi":"10.1503/cmaj.170116","title":"Geographic location as a modifiable cardiac risk factor","year":2017,"lang":"en","type":"letter","venue":"Canadian Medical Association Journal","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Population; Risk factor; Disease; Environmental health; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003533295,0.0001743419,0.000267515,0.0005433021,0.0009217541,0.000605617,0.0005679723,0.002370203,0.008799281],"category_scores_gemma":[0.003478135,0.0001002854,0.0004567103,0.001139489,0.0004103532,0.0004273623,0.0004201166,0.002696769,0.0009221085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173181,"about_ca_system_score_gemma":0.001598211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07966116,"about_ca_topic_score_gemma":0.1417597,"domain_scores_codex":[0.9994869,0.0001117627,0.00004389146,0.00009098312,0.0001576009,0.0001087838],"domain_scores_gemma":[0.9987679,0.0004223666,0.00029019,0.00008561834,0.0002419943,0.0001919596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002355703,0.00008756166,0.7213309,0.0002406737,0.0001716964,0.002720721,0.0002516707,0.0002015616,0.0005035833,0.002997439,0.2172312,0.05402731],"study_design_scores_gemma":[0.0001056381,0.0001731687,0.8744645,0.0009714714,0.0004843283,0.007904227,0.001163991,0.001818735,0.0004302967,0.005857926,0.1065461,0.00007956471],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2273451,0.03316407,0.001410146,0.6307884,0.007415432,0.00008538211,0.009337604,0.0001319008,0.090322],"genre_scores_gemma":[0.9065309,0.009722966,0.0009626258,0.06134621,0.01071299,0.00007255434,0.002149752,0.00002847397,0.008473658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07966116,"threshold_uncertainty_score":0.1583949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01548074806794916,"score_gpt":0.2928012391357753,"score_spread":0.2773204910678262,"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."}}