{"id":"W3128813618","doi":"10.1186/s12889-021-10295-w","title":"A data quality assessment to inform hypertension surveillance using primary care electronic medical record data from Alberta, Canada","year":2021,"lang":"en","type":"article","venue":"BMC Public Health","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Public Health Agency; Public Health Agency of Canada","keywords":"Medicine; Biostatistics; Context (archaeology); Blood pressure; Medical record; Data quality; Body mass index; Family medicine; Environmental health; Pediatrics; Epidemiology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01396682,0.0004627534,0.001542873,0.0001425433,0.001710647,0.00006874726,0.002891429,0.0004927748,0.00105245],"category_scores_gemma":[0.007655099,0.0004441982,0.00005268999,0.001297043,0.00003974222,0.0006857919,0.003542715,0.002543194,0.0001020065],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01857829,"about_ca_system_score_gemma":0.4643688,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9824807,"about_ca_topic_score_gemma":0.9993581,"domain_scores_codex":[0.9809857,0.007323821,0.003256796,0.002025547,0.002535418,0.003872733],"domain_scores_gemma":[0.9833217,0.005059569,0.001041133,0.006848368,0.0009376997,0.002791496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000107406,0.0002725765,0.5938935,0.006197974,0.0001686521,0.000049586,0.001351208,0.000004949199,0.0000256181,0.001049507,0.3070706,0.08980852],"study_design_scores_gemma":[0.001200598,0.00008452855,0.139511,0.0005177496,0.000007736377,0.00002136963,0.002898473,0.00603003,2.380128e-7,0.00001698537,0.8492988,0.0004125275],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7249654,0.009689003,0.02389682,0.2005601,0.01114082,0.007319333,0.01330949,0.0004861513,0.008632873],"genre_scores_gemma":[0.6947313,0.002224977,0.02285771,0.1602214,0.004862669,0.0003881655,0.1120816,0.000370412,0.002261804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5422282,"threshold_uncertainty_score":0.9998607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3234196150421889,"score_gpt":0.495052423086589,"score_spread":0.1716328080444001,"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."}}