{"id":"W1936565640","doi":"10.1183/13993003/erj.42.suppl_57.p1351","title":"Body composition analysis using computed tomography image in patients with advanced lung cancer","year":2013,"lang":"en","type":"article","venue":"European Respiratory Journal","topic":"Nutrition and Health in Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"","keywords":"Medicine; Sarcopenia; Lung cancer; Body mass index; Lung; Cancer; Radiology; Computed tomography; Lumbar; Nuclear medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002599806,0.0002309049,0.0002959303,0.0009768147,0.0002595477,0.0003992586,0.0001556262,0.0003720827,0.001187737],"category_scores_gemma":[0.0009895802,0.0001211123,0.0002209189,0.0006066285,0.0001917916,0.0002422079,0.00033352,0.0002908228,0.0002581048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001741533,"about_ca_system_score_gemma":0.0001260663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001528592,"about_ca_topic_score_gemma":0.002115813,"domain_scores_codex":[0.9998584,0.00003093788,0.00001803445,0.00003258439,0.00003553837,0.00002455123],"domain_scores_gemma":[0.9995827,0.00008205828,0.0001890368,0.0000185989,0.00005048594,0.00007708941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001110186,0.00001338714,0.9984068,0.000005204976,0.000009593422,0.0001007219,0.00003901209,0.00002199228,0.0005073457,0.000002122002,0.00001614602,0.0007665957],"study_design_scores_gemma":[0.000002820446,0.00009982452,0.9991884,0.000001999736,0.000007474333,0.0004151776,0.00007991135,0.00007704974,0.00008502982,0.000004673662,0.0000365626,0.000001178604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996184,0.0001034705,0.00003196489,0.00001276008,0.000001828272,0.000005102715,0.00007185122,0.000001329159,0.0001533275],"genre_scores_gemma":[0.9996691,0.0000502795,0.00006254693,0.000008987707,0.000003561855,0.000005264758,0.0001243435,5.544544e-7,0.00007538552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001528592,"threshold_uncertainty_score":0.003973365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01699065003033902,"score_gpt":0.3090043504443967,"score_spread":0.2920137004140577,"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."}}