{"id":"W3081046955","doi":"10.1136/bmjhci-2020-100161","title":"Primary care EMR and administrative data linkage in Alberta, Canada: describing the suitability for hypertension surveillance","year":2020,"lang":"en","type":"article","venue":"BMJ Health & Care Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions; Public Health Agency; Public Health Agency of Canada; Alberta Health Services","keywords":"Medicine; Cohort; Family medicine; Health care; Record linkage; Population; Medical emergency; Ambulatory care; Medical record; Pharmacy; Emergency medicine; Environmental health; Internal medicine","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":[0.02220692,0.0002670896,0.0002652806,0.002869679,0.002398186,0.003636032,0.001966077,0.0006391488,0.0006478],"category_scores_gemma":[0.0596463,0.0003229127,0.0004122562,0.009451345,0.00107411,0.0008440905,0.002241625,0.0005316176,0.0001005227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03993616,"about_ca_system_score_gemma":0.08674191,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9739368,"about_ca_topic_score_gemma":0.9794006,"domain_scores_codex":[0.9755231,0.005969187,0.001821018,0.001464417,0.0122215,0.003000774],"domain_scores_gemma":[0.9685209,0.009768851,0.005161937,0.001249574,0.0136728,0.001625953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001133985,0.00003897413,0.9548951,0.0001774449,0.00005500522,0.0003469693,0.00286187,0.0009603786,0.0003000679,0.00061226,0.00196473,0.0376739],"study_design_scores_gemma":[0.00001584856,0.00005247163,0.9865031,0.0002143037,0.00004382526,0.0002155843,0.00478635,0.002908272,0.0002398068,0.0001287467,0.004869722,0.00002188528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9682783,0.003321145,0.004493755,0.006266639,0.00007412826,0.001282235,0.004645349,0.0001545493,0.01148376],"genre_scores_gemma":[0.9885951,0.001098904,0.006573151,0.000556262,0.00002552795,0.000217107,0.002043447,0.00002046433,0.0008699212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03993616,"threshold_uncertainty_score":0.2897585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2450275826951258,"score_gpt":0.4239528738553403,"score_spread":0.1789252911602144,"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."}}