{"id":"W2035087424","doi":"10.1016/j.acra.2010.01.002","title":"Predicting Postoperative FEV1 Using Spiral Computed Tomography","year":2010,"lang":"en","type":"article","venue":"Academic Radiology","topic":"Lung Cancer Diagnosis and Treatment","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; London Health Sciences Centre; Western University","funders":"","keywords":"Medicine; Radiology; Scintigraphy; Perfusion scanning; Spiral computed tomography; Perioperative; Lung; Subtraction; Perfusion; Lung cancer; Nuclear medicine; Pulmonary function testing; Context (archaeology); Computed tomography; 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":[0.0004806329,0.0005450886,0.0004288608,0.0007847557,0.0001887831,0.0006114315,0.0003336774,0.0007130339,0.001120029],"category_scores_gemma":[0.004136334,0.0002062924,0.0004110138,0.0003932034,0.0002833863,0.0004480616,0.0002226973,0.0005164382,0.0004226468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003623955,"about_ca_system_score_gemma":0.0004846693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002394276,"about_ca_topic_score_gemma":0.003160665,"domain_scores_codex":[0.9998185,0.00004676696,0.00002486685,0.00002126153,0.00005433725,0.00003424662],"domain_scores_gemma":[0.9983653,0.0008392775,0.0002316792,0.00007462883,0.0002438434,0.0002451276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000427343,0.00006722208,0.9897485,0.000008730371,0.00001842173,0.000109788,0.00001276415,0.0003138495,0.0007192598,0.00001986107,0.0001844326,0.008369819],"study_design_scores_gemma":[0.00004605594,0.001147017,0.9815885,0.0000233181,0.0001258253,0.001703932,0.000185259,0.01181601,0.002526227,0.0002129847,0.0006091668,0.00001572611],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978598,0.0006449075,0.0003962364,0.0001459841,0.00002923343,0.000007925713,0.00008887334,0.00002579605,0.0008012435],"genre_scores_gemma":[0.9989359,0.000210604,0.0004595165,0.00002715812,0.0000222972,0.000004124106,0.0001322801,0.000003057373,0.0002050559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002394276,"threshold_uncertainty_score":0.004760623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02100600525276611,"score_gpt":0.3163601824794474,"score_spread":0.2953541772266812,"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."}}