{"id":"W2618217372","doi":"10.1200/jco.2013.31.15_suppl.1592","title":"A survey of clinical prediction tools in colorectal and lung cancers and melanoma.","year":2013,"lang":"en","type":"article","venue":"Journal of Clinical Oncology","topic":"Radiomics and Machine Learning in Medical Imaging","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Colorectal cancer; Lung cancer; Oncology; Population; Disease; Internal medicine; Stage (stratigraphy); Cancer; Medical physics","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":[0.02028359,0.0004699823,0.0009575553,0.01924409,0.0003462633,0.00183458,0.001227771,0.001004084,0.002895457],"category_scores_gemma":[0.1033093,0.0002883718,0.001568304,0.01828619,0.0006412596,0.002946075,0.001186246,0.0008042346,0.0006440013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001093954,"about_ca_system_score_gemma":0.00294418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002097899,"about_ca_topic_score_gemma":0.002662743,"domain_scores_codex":[0.9902658,0.002972574,0.003166824,0.0005790361,0.002831578,0.0001843033],"domain_scores_gemma":[0.797771,0.1796636,0.01257988,0.001338694,0.007557657,0.001089182],"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":[0.0004025612,0.0001437806,0.1131902,0.03234108,0.0004982771,0.0006710732,0.001203048,0.000741169,0.0003060629,0.001611078,0.0146664,0.8342254],"study_design_scores_gemma":[0.0003181956,0.001731703,0.5446886,0.1475051,0.003515384,0.01205038,0.004573054,0.006128938,0.002032528,0.006178991,0.2710131,0.0002639753],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1331595,0.820129,0.006284525,0.01127173,0.0003814728,0.0004722028,0.0131885,0.0004493095,0.01466369],"genre_scores_gemma":[0.488511,0.4610207,0.02510391,0.00436322,0.0004332098,0.000866195,0.01847474,0.0001779848,0.001048933],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02028359,"threshold_uncertainty_score":0.1072712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1014615407278781,"score_gpt":0.4793669966953422,"score_spread":0.3779054559674642,"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."}}