{"id":"W4319723082","doi":"10.1186/s12877-023-03752-1","title":"Multicompartment body composition analysis in older adults: a cross-sectional study","year":2023,"lang":"en","type":"article","venue":"BMC Geriatrics","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geomechanica (Canada)","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Anthropometry; Medicine; Linear regression; Multivariate statistics; Lean body mass; Sarcopenia; Body mass index; Cross-sectional study; Statistics; Internal medicine; Mathematics; Body weight; Pathology","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":[0.0005171809,0.0001066212,0.0002882839,0.0009470739,0.0001106832,0.00003880238,0.00005004544,0.00006393924,0.0001734623],"category_scores_gemma":[0.00003451265,0.0001048781,0.0001206287,0.00232747,0.00001560938,0.00004890926,0.00003351742,0.0001578437,0.0001621585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001934204,"about_ca_system_score_gemma":0.00006133351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001274614,"about_ca_topic_score_gemma":0.0001708966,"domain_scores_codex":[0.9984869,0.00007821614,0.0005014596,0.0003030878,0.0003762808,0.0002540237],"domain_scores_gemma":[0.9993773,0.00009815608,0.00008598295,0.0001976731,0.0001168878,0.0001239717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000291369,0.001274736,0.9971065,0.0001615295,0.00005739967,0.00003470046,0.0004230624,0.0003703317,0.00004659787,0.00002404071,0.0001697493,0.00003998798],"study_design_scores_gemma":[0.005981413,0.0001174587,0.9808263,0.00002269654,0.0001349147,0.000004794136,0.0003519731,0.01235439,0.0000162558,0.00001417045,0.0000839264,0.000091751],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979232,0.00006067479,0.0004357033,0.0001224435,0.0002783697,0.000911593,0.00001798596,0.0001535705,0.00009648929],"genre_scores_gemma":[0.9980333,0.0000183251,0.001071919,0.0001203853,0.0002035142,0.0001184586,0.0002871618,0.00001224087,0.0001346948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01628024,"threshold_uncertainty_score":0.4276803,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04865648045558843,"score_gpt":0.3860677004830942,"score_spread":0.3374112200275058,"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."}}