{"id":"W3117466965","doi":"10.1016/j.cjco.2020.12.019","title":"CREATE: A New Data Resource to Support Cardiac Precision Health","year":2020,"lang":"en","type":"article","venue":"CJC Open","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Health Services","funders":"Canadian Institutes of Health Research; University of Calgary","keywords":"Database; Record linkage; Big data; Medicine; Health care; Analytics; Population; Computer science; Data science; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01450378,0.0009516702,0.001100732,0.007080942,0.001600077,0.007205966,0.003639763,0.001387075,0.02373748],"category_scores_gemma":[0.0507779,0.0009765876,0.001019345,0.007142413,0.001306028,0.008116704,0.01078977,0.002001776,0.01093856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001833898,"about_ca_system_score_gemma":0.008640138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004720107,"about_ca_topic_score_gemma":0.007206041,"domain_scores_codex":[0.9913191,0.002005993,0.001392394,0.001480196,0.003332507,0.0004696705],"domain_scores_gemma":[0.9335523,0.02199801,0.006499952,0.02253005,0.00639989,0.009019802],"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":[0.001603162,0.0003212898,0.04115192,0.001307574,0.0003258776,0.0007259474,0.001532217,0.002842774,0.005731465,0.03635114,0.6657925,0.2423142],"study_design_scores_gemma":[0.0005262624,0.0002224378,0.02378637,0.0005588338,0.0001738524,0.001272612,0.0005737304,0.01089732,0.007616369,0.01629209,0.9378491,0.0002309383],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.04428593,0.00350288,0.2684554,0.01489304,0.002167872,0.003584613,0.364988,0.2074996,0.09062272],"genre_scores_gemma":[0.1257335,0.002257355,0.3083235,0.004677341,0.00196075,0.002510897,0.5234404,0.01483931,0.01625688],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02373748,"threshold_uncertainty_score":0.07940984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3028974602589314,"score_gpt":0.5365184956365843,"score_spread":0.2336210353776529,"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."}}