{"id":"W4390431080","doi":"10.14740/cr1569","title":"Is the Blood Pressure-Enabled Smartwatch Ready to Drive Precision Medicine? Supporting Findings From a Validation Study","year":2023,"lang":"en","type":"article","venue":"Cardiology Research","topic":"Blood Pressure and Hypertension Studies","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Blood pressure; Medical instrumentation; Smartwatch; Anthropometry; Sphygmomanometer; Internal medicine; Wrist; Physical therapy; Cardiology; Wearable computer; Surgery; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.300409,0.001846705,0.001572537,0.001956676,0.001757974,0.005466285,0.00595489,0.003894595,0.005743114],"category_scores_gemma":[0.4426298,0.001037301,0.004937278,0.002098549,0.005940095,0.006598227,0.003659094,0.002298299,0.002406533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00212013,"about_ca_system_score_gemma":0.01068443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005661229,"about_ca_topic_score_gemma":0.004724973,"domain_scores_codex":[0.8211575,0.1028625,0.01902524,0.01377769,0.03943991,0.003737187],"domain_scores_gemma":[0.3010916,0.5147216,0.03453523,0.04464502,0.1010318,0.003974824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01096442,0.004338458,0.7651261,0.00996475,0.004090592,0.001206392,0.01927877,0.001539343,0.003946653,0.007104652,0.00690138,0.1655384],"study_design_scores_gemma":[0.002807158,0.03204603,0.7815325,0.03108669,0.01425116,0.004990724,0.030558,0.01938987,0.01815726,0.007892787,0.05670009,0.0005877687],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8344101,0.01173846,0.08009174,0.01906171,0.002092978,0.01096098,0.0047181,0.0003389322,0.03658703],"genre_scores_gemma":[0.9439116,0.002084137,0.0431637,0.003852086,0.0004290567,0.002615951,0.002774828,0.00009770838,0.001070992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.300409,"threshold_uncertainty_score":0.8627203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1738043914097878,"score_gpt":0.4379615097111346,"score_spread":0.2641571183013468,"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."}}