{"id":"W2604828715","doi":"10.1093/eurheartj/ehx088","title":"Status and future of genomics in blood pressure","year":2017,"lang":"en","type":"article","venue":"European Heart Journal","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"","keywords":"Medicine; Genomics; Blood pressure; Computational biology; Intensive care medicine; Internal medicine; Genetics; Genome; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001023192,0.00009199114,0.0001259613,0.00002977373,0.0003059637,0.00006946234,0.0001907576,0.00002396142,0.0005261548],"category_scores_gemma":[0.00005576393,0.00008529117,0.00002800952,0.00002268142,0.0001789901,0.000267899,0.0002496644,0.0003753589,0.0000840944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002664755,"about_ca_system_score_gemma":0.00001316623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005451874,"about_ca_topic_score_gemma":0.000025186,"domain_scores_codex":[0.9988557,0.0002554682,0.0002097381,0.0002064545,0.0001807591,0.0002919327],"domain_scores_gemma":[0.999301,0.00002254043,0.0001852427,0.000288867,0.000003316791,0.0001990042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001191728,0.0000526497,0.9667226,0.00000925984,0.00001263335,0.00008577679,0.0008999885,0.00007699292,0.007813523,0.000008989377,0.0002936313,0.02401201],"study_design_scores_gemma":[0.0004469435,0.00005193184,0.8544266,0.0000186524,0.0000163871,0.0001012658,0.00008803396,0.0000257486,0.0003588935,0.00003778536,0.1443536,0.0000740782],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792484,0.0006198125,0.00001217385,0.0006596592,0.0001077454,0.00009732403,0.000005170426,0.00000392695,0.01924577],"genre_scores_gemma":[0.9963264,0.001861717,0.001125424,0.0002352447,0.0002545363,3.609697e-7,3.672983e-7,0.00001996991,0.0001759611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.14406,"threshold_uncertainty_score":0.5761026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02369731801330894,"score_gpt":0.2687690109195879,"score_spread":0.2450716929062789,"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."}}