{"id":"W2941430070","doi":"10.1097/hjh.0000000000002112","title":"Optimizing observer performance of clinic blood pressure measurement","year":2019,"lang":"en","type":"article","venue":"Journal of Hypertension","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta; University of Calgary; University of Alberta","funders":"Servier; Hypertension Canada; International Society of Hypertension; Novo Nordisk Fonden; American Heart Association","keywords":"Medicine; Observer (physics); Sphygmomanometer; Certification; Units of measurement; Blood pressure; Workstation; Task (project management); Observational error; Position statement; Reliability engineering; Computer science; Statistics; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.07904565,0.0008667937,0.0009807321,0.001266195,0.001031092,0.001898712,0.001470942,0.001192918,0.002352809],"category_scores_gemma":[0.1578408,0.000504143,0.0008884942,0.001008634,0.0006955025,0.001258736,0.001913755,0.0009656616,0.002325833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001163099,"about_ca_system_score_gemma":0.002060914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003699157,"about_ca_topic_score_gemma":0.005264709,"domain_scores_codex":[0.9246562,0.05340178,0.007416288,0.003912679,0.009540746,0.001072332],"domain_scores_gemma":[0.8680262,0.06169168,0.010934,0.01256619,0.04537676,0.001405168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003536847,0.0005166856,0.2753288,0.002530069,0.0008676935,0.0003349524,0.005194095,0.005407277,0.02730441,0.002192889,0.03336148,0.6434247],"study_design_scores_gemma":[0.0007242599,0.003886829,0.6758806,0.002671975,0.001794668,0.002602446,0.003589707,0.09023429,0.08706495,0.009320094,0.121646,0.000584208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3065738,0.006476019,0.6399546,0.005399158,0.002914399,0.003568748,0.001391261,0.004362504,0.02935946],"genre_scores_gemma":[0.6291061,0.001142375,0.3588094,0.001561078,0.000514622,0.002359652,0.001117619,0.000826208,0.00456298],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07904565,"threshold_uncertainty_score":0.4180383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.088819051273062,"score_gpt":0.2656346212117481,"score_spread":0.1768155699386861,"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."}}