{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008620519,0.000155623,0.0009791709,0.0001411368,0.00004693843,0.000006909293,0.000113011,0.0001095025,0.000189585],"category_scores_gemma":[0.000130226,0.0001012702,0.0002838944,0.0001256827,0.00003823425,0.0001648601,0.00006814386,0.0003493183,0.00003317326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005361405,"about_ca_system_score_gemma":0.0001176985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004880807,"about_ca_topic_score_gemma":4.719729e-7,"domain_scores_codex":[0.9979376,0.00005016693,0.0007464846,0.0001541044,0.0009239886,0.0001876411],"domain_scores_gemma":[0.9972183,0.00007284868,0.0005206578,0.0003049938,0.001775705,0.000107475],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003253152,0.001754949,0.1257913,0.001460106,0.00662636,0.0003716051,0.0005372863,0.0002560299,0.8248355,0.000009440726,0.03083606,0.004268116],"study_design_scores_gemma":[0.03255647,0.01687408,0.4713937,0.01022623,0.04920617,0.00927113,0.001340347,0.00236144,0.2680947,0.00002768479,0.1377424,0.0009056262],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515931,0.04593724,0.000003609081,0.0008203662,0.0005680484,0.0001884871,9.007709e-7,0.00001049688,0.0008777343],"genre_scores_gemma":[0.9940748,0.00193652,0.002114372,0.001041226,0.0001980998,7.028071e-7,5.396139e-7,0.00002031856,0.0006134575],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5567408,"threshold_uncertainty_score":0.412968,"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."}}