{"id":"W3193388705","doi":"10.3390/ijerph18178927","title":"Predictive Performance and Optimal Cut-Off Points of Blood Pressure for Identifying Arteriosclerosis among Adults in Eastern China","year":2021,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Social Science Fund of China; Ningbo University","keywords":"Arteriosclerosis; Blood pressure; China; Medicine; Internal medicine; Cardiology; Demography; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00266242,0.0004607096,0.0004373469,0.001442405,0.0003807563,0.0007582873,0.0003002385,0.0004849487,0.0005411691],"category_scores_gemma":[0.005366031,0.0002365288,0.0004577289,0.0008951562,0.0003493293,0.0004876237,0.0004567165,0.0005154373,0.000108714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003411467,"about_ca_system_score_gemma":0.0006602951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008903462,"about_ca_topic_score_gemma":0.008986096,"domain_scores_codex":[0.9988528,0.0003691463,0.0001912044,0.0001866163,0.0002496942,0.0001505037],"domain_scores_gemma":[0.9976959,0.0007083718,0.0005557254,0.0001441452,0.0005565512,0.00033929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007101404,0.00001804549,0.996003,0.00001425889,0.00004044221,0.00008911191,0.00009762299,0.0001662673,0.0001513969,0.0000591426,0.00006936582,0.003220428],"study_design_scores_gemma":[0.00001116498,0.00008010639,0.9954545,0.00002058731,0.00007988149,0.0001642583,0.0002529662,0.003360566,0.0001672987,0.0001847103,0.0002150688,0.000008789207],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984618,0.0005083801,0.0004218916,0.00009626354,0.00001497011,0.000007857607,0.00007616322,0.000006713165,0.0004060204],"genre_scores_gemma":[0.9994168,0.0001320698,0.000249155,0.00001812019,0.00001748657,0.000005032382,0.00009612799,0.00000131285,0.00006388962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008903462,"threshold_uncertainty_score":0.01770329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03950826475221358,"score_gpt":0.3486187447627455,"score_spread":0.3091104800105319,"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."}}