{"id":"W2300594175","doi":"10.1200/jop.2015.007062","title":"ReCAP: Oncologists’ Selection of Genetic and Molecular Testing in the Evolving Landscape of Stage II Colorectal Cancer","year":2016,"lang":"en","type":"article","venue":"Journal of Oncology Practice","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; U.S. Public Health Service","keywords":"Medicine; Colorectal cancer; Selection (genetic algorithm); Genetic testing; Bioinformatics; Cancer; Computational biology; Internal medicine; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001872701,0.0001126302,0.0004528855,0.0001877287,0.00004271861,0.000004817845,0.0001351376,0.0001690735,0.0001146306],"category_scores_gemma":[0.008990556,0.00006558922,0.00005808187,0.0003774932,0.0001805816,0.0001478802,0.00005861368,0.0004074344,3.485729e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003345156,"about_ca_system_score_gemma":0.00107241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001117246,"about_ca_topic_score_gemma":0.0001098562,"domain_scores_codex":[0.9981369,0.0004853068,0.0007001775,0.0001393132,0.000354461,0.0001838805],"domain_scores_gemma":[0.9943207,0.003249795,0.001431573,0.0001000638,0.0008382326,0.00005963987],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00254773,0.0004462636,0.3518819,0.00008008321,0.0001603032,0.0002235206,0.001141107,0.0001265413,0.6062305,0.00001312959,0.0005315042,0.03661741],"study_design_scores_gemma":[0.006857127,0.02685251,0.8383763,0.0005850102,0.0008202434,0.005761272,0.002395147,0.0003313377,0.1067476,0.0001176621,0.0109632,0.0001925107],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9905369,0.001929636,0.0001473579,0.003995714,0.0002605431,0.0002507577,0.000002808998,0.000003679811,0.002872636],"genre_scores_gemma":[0.9839626,0.0006557596,0.01489913,0.0003098392,0.0001142019,0.00001050803,1.142722e-7,0.00001205734,0.0000358115],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4994829,"threshold_uncertainty_score":0.9993572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03403582816558599,"score_gpt":0.3530219242349733,"score_spread":0.3189860960693873,"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."}}