{"id":"W4393928418","doi":"10.1093/eurjcn/zvae040","title":"Optimizing sarcopenia screening in older patients with cardiovascular disease: insights and cut-off considerations","year":2024,"lang":"en","type":"article","venue":"European Journal of Cardiovascular Nursing","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Sarcopenia; Intensive care medicine; Disease; Gerontology; Physical therapy; Internal medicine","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":[0.0014343,0.0002041346,0.0006462018,0.000522831,0.0001740262,0.0001740777,0.00005920842,0.00002750159,0.00001502678],"category_scores_gemma":[0.0001098202,0.0001659086,0.0006415862,0.0003117237,0.0001173039,0.000371074,0.00002309189,0.0005591625,0.000005020298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001059552,"about_ca_system_score_gemma":0.0001504341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002300562,"about_ca_topic_score_gemma":2.754765e-7,"domain_scores_codex":[0.9974161,0.0006002593,0.0005600511,0.0003130916,0.0008370751,0.0002733993],"domain_scores_gemma":[0.9988285,0.00007390759,0.00007748288,0.0003530064,0.0002794732,0.0003876395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001163698,0.0006778692,0.01291398,0.002149711,0.01541716,0.04219186,0.01289538,0.04338252,0.00008128087,0.0005140189,0.002349958,0.8662626],"study_design_scores_gemma":[0.03202104,0.0009647568,0.5090597,0.07520878,0.01209489,0.00634478,0.001781475,0.005920878,0.0001982473,0.0002919592,0.3547584,0.001355046],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.4410278,0.5018655,0.05076617,0.001290171,0.0008017957,0.0007579183,0.00000521497,0.00008750011,0.003397888],"genre_scores_gemma":[0.9828942,0.001997897,0.01438755,0.0001776478,0.0004411005,0.000001607687,0.000007828739,0.00007748949,0.00001470883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8649075,"threshold_uncertainty_score":0.6765555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02281847855818035,"score_gpt":0.2664589903461186,"score_spread":0.2436405117879383,"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."}}