{"id":"W2083919643","doi":"10.1097/mbp.0b013e32834b45d2","title":"Can blood pressure measurements taken in the physician’s office avoid the ‘white coat’ bias?","year":2011,"lang":"en","type":"article","venue":"Blood Pressure Monitoring","topic":"Healthcare Technology and Patient Monitoring","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; Ministerio de Ciencia e Innovación","keywords":"Medicine; White coat hypertension; Blood pressure; Ambulatory blood pressure; Ambulatory; Masked Hypertension; Gold standard (test); Diastole; White coat; Physician Office; Cardiology; Internal medicine; Health care","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001311836,0.0003949756,0.0004728362,0.0001627986,0.0004379843,0.00004403383,0.0008143763,0.0003643902,0.00001898092],"category_scores_gemma":[0.0002239573,0.000258115,0.0001394496,0.0005494207,0.0001444613,0.0001469316,0.0001453374,0.001441503,0.0000177519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001361012,"about_ca_system_score_gemma":0.0001313969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008631459,"about_ca_topic_score_gemma":0.00009299358,"domain_scores_codex":[0.9967675,0.000491437,0.0005501034,0.0005534501,0.0008590707,0.0007784129],"domain_scores_gemma":[0.9979814,0.0001992226,0.0002584349,0.001219152,0.0002044317,0.0001373225],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001763388,0.0008639081,0.9797652,0.0005195734,0.001297603,0.0001281282,0.01008155,0.000028176,0.002357837,0.00007962858,0.0001868308,0.004515219],"study_design_scores_gemma":[0.005919357,0.001258437,0.753312,0.002223037,0.01278555,0.0001883825,0.005779326,0.0000279751,0.183356,0.000218939,0.03395141,0.000979585],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9603767,0.02351431,0.00001101453,0.001826793,0.002190221,0.003050093,0.00003715032,0.0004880339,0.008505728],"genre_scores_gemma":[0.9967328,0.00009380294,0.0002684901,0.000296278,0.001641956,0.000389613,0.000006954477,0.00005812883,0.0005119778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2264532,"threshold_uncertainty_score":0.9999871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1271028053804914,"score_gpt":0.2978316403781548,"score_spread":0.1707288349976634,"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."}}