{"id":"W2898106531","doi":"10.1139/apnm-2018-0276","title":"Ethnic differences in fat and muscle mass and their implication for interpretation of bioelectrical impedance vector analysis","year":2018,"lang":"en","type":"article","venue":"Applied Physiology Nutrition and Metabolism","topic":"Body Composition Measurement Techniques","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bioelectrical impedance analysis; Body mass index; Muscle mass; Ethnic group; Phase angle (astronomy); Medicine; Obesity; Anthropometry; Demography; Fat mass; Internal medicine; Endocrinology; Physiology; Gerontology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001248243,0.00009867126,0.0003629049,0.0002286221,0.00003757892,0.000005200915,0.00002896853,0.00009253712,0.000004673542],"category_scores_gemma":[0.00001609074,0.00007967081,0.00003768877,0.000297128,0.0001927194,0.00003880665,0.00001351655,0.00006972277,1.836911e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008878073,"about_ca_system_score_gemma":0.000006871497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007888986,"about_ca_topic_score_gemma":0.000005052306,"domain_scores_codex":[0.9993709,0.00003206311,0.0001985683,0.0002441839,0.00004736617,0.0001068906],"domain_scores_gemma":[0.9995863,0.00008765108,0.00009149291,0.00010105,0.00009217066,0.00004133486],"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":[0.0001904695,0.00008018487,0.0002725912,0.00006828423,0.00006761652,1.981343e-8,0.0002363257,2.344811e-8,0.9769207,0.004098995,0.00001875973,0.01804608],"study_design_scores_gemma":[0.001632327,0.0001137821,0.755855,0.000029222,0.0002237922,0.000001105142,0.00009771457,0.001890122,0.2284402,0.01147317,0.0001578885,0.00008578474],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847568,0.001747848,0.01258148,0.0002399221,0.00001627501,0.0005874059,0.00001432492,0.0000298461,0.00002610458],"genre_scores_gemma":[0.9957277,0.001268471,0.002491179,0.0001455459,0.0000733233,0.0002368479,0.00004954005,0.000005817295,0.000001527793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7555823,"threshold_uncertainty_score":0.3248881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02468453970136926,"score_gpt":0.2964762455792946,"score_spread":0.2717917058779253,"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."}}