{"id":"W2801796280","doi":"10.1017/s0029665118000046","title":"A window beneath the skin: how computed tomography assessment of body composition can assist in the identification of hidden wasting conditions in oncology that profoundly impact outcomes","year":2018,"lang":"en","type":"review","venue":"Proceedings of The Nutrition Society","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Science Foundation Ireland; Health Research Board","keywords":"Sarcopenia; Wasting; Medicine; Cachexia; Skeletal muscle; Cancer; Intensive care medicine; Disease; Muscle mass; Lean body mass; Internal medicine; Oncology; Physical medicine and rehabilitation; Body weight","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":[0.004883021,0.00128331,0.001346726,0.003928856,0.0006441213,0.005900871,0.001264776,0.002512735,0.005172543],"category_scores_gemma":[0.01829698,0.0008372164,0.001123683,0.001574155,0.001784757,0.005407718,0.002534705,0.003830611,0.003108221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007654389,"about_ca_system_score_gemma":0.001612961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003648486,"about_ca_topic_score_gemma":0.00600698,"domain_scores_codex":[0.9976063,0.001265355,0.0001566917,0.0003129483,0.0005397201,0.0001189363],"domain_scores_gemma":[0.9931173,0.003693425,0.0005098864,0.0005200882,0.001673238,0.0004860036],"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":[0.000455046,0.000195857,0.03284343,0.001981511,0.0003705428,0.001834813,0.001192019,0.00191188,0.005550821,0.01043423,0.06702635,0.8762034],"study_design_scores_gemma":[0.0002386831,0.001434383,0.07991876,0.02448759,0.001781668,0.03227628,0.0083715,0.03490649,0.01151124,0.1287326,0.6752345,0.001106306],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03652121,0.4945248,0.2865018,0.1119152,0.01634361,0.0008111004,0.00205169,0.005204494,0.04612602],"genre_scores_gemma":[0.2522154,0.3692408,0.3187473,0.02712407,0.01659736,0.0005995796,0.001172066,0.001296101,0.01300744],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005900871,"threshold_uncertainty_score":0.02582419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0781246253476378,"score_gpt":0.4307965332957195,"score_spread":0.3526719079480817,"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."}}