{"id":"W3084195048","doi":"10.1007/s40618-020-01417-z","title":"Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype","year":2020,"lang":"en","type":"article","venue":"Journal of Endocrinological Investigation","topic":"Diabetes, Cardiovascular Risks, and Lipoproteins","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"National Social Science Fund of China; National Natural Science Foundation of China","keywords":"Medicine; Waist; Body mass index; Anthropometry; Quartile; Receiver operating characteristic; Internal medicine; Odds ratio; Logistic regression; Multivariate analysis; Obesity; Confidence interval","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":[],"consensus_categories":[],"category_scores_codex":[0.0004896381,0.0002070079,0.000783348,0.0001181731,0.0001225076,0.00006782381,0.0002683293,0.0001124662,0.00006167995],"category_scores_gemma":[0.002434042,0.0001206235,0.000791735,0.000461082,0.0001754979,0.0002532138,0.00007263703,0.0005996504,0.00001318243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002710547,"about_ca_system_score_gemma":0.0002322562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001102813,"about_ca_topic_score_gemma":0.000005623245,"domain_scores_codex":[0.9979183,0.000167181,0.0006748327,0.0002220687,0.000646423,0.0003711587],"domain_scores_gemma":[0.9983963,0.0001687956,0.00035354,0.0002333177,0.000393939,0.0004540546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001325144,0.00007821874,0.01398594,0.0001232554,0.002069907,0.000134169,0.0006479224,0.001075813,0.007366854,0.003469625,0.01001683,0.9597063],"study_design_scores_gemma":[0.007214815,0.001643564,0.4757016,0.0001168148,0.002021617,0.0004408077,0.0001679329,0.001274439,0.01745764,0.003792568,0.4898069,0.0003612732],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8855964,0.008870834,0.06802876,0.03558054,0.0004132027,0.0009734725,0.00000952657,0.00007833005,0.0004489197],"genre_scores_gemma":[0.9668736,0.0003051759,0.0210536,0.005976846,0.00559094,0.00002440675,0.00001123586,0.00002719578,0.0001369463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.959345,"threshold_uncertainty_score":0.4918883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05372979172676707,"score_gpt":0.2707140262866007,"score_spread":0.2169842345598336,"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."}}