{"id":"W3040806267","doi":"10.1002/ijc.33191","title":"Prediction of colorectal cancer risk based on profiling with common genetic variants","year":2020,"lang":"en","type":"review","venue":"International Journal of Cancer","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"Medical Research Council; Medical Research Council Canada; Cancer Research UK; Wellcome Trust","keywords":"Colorectal cancer; Profiling (computer programming); Computational biology; Biology; Oncology; Genetics; Medicine; Bioinformatics; Cancer; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005377705,0.001018312,0.001009247,0.002860228,0.0002762027,0.00118192,0.0004903542,0.0005981962,0.001597254],"category_scores_gemma":[0.01447388,0.0003366396,0.00240998,0.003111034,0.0003173656,0.0005633708,0.0007918095,0.0008335217,0.0002794949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002447153,"about_ca_system_score_gemma":0.0003093085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002990525,"about_ca_topic_score_gemma":0.002948036,"domain_scores_codex":[0.9971712,0.001449722,0.0002638042,0.0005937941,0.0004082883,0.000113211],"domain_scores_gemma":[0.9901935,0.005909417,0.002407379,0.0007848077,0.0004972483,0.0002075274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009509929,0.00004548154,0.9649475,0.0002636612,0.004420422,0.000202437,0.00004146578,0.005686504,0.002046635,0.0001655274,0.0003888448,0.02084054],"study_design_scores_gemma":[0.0001488871,0.001055859,0.9051457,0.0002082171,0.009182035,0.00131029,0.0001317152,0.0749225,0.003255273,0.002822796,0.001750904,0.00006578652],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.958178,0.01313271,0.02436842,0.0005974604,0.00009977059,0.00007264657,0.002083945,0.0002013952,0.00126573],"genre_scores_gemma":[0.9960274,0.0005993051,0.002743735,0.00003608238,0.0000240576,0.00001071454,0.000421949,0.00000743593,0.0001293447],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005377705,"threshold_uncertainty_score":0.02844042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03889491159601034,"score_gpt":0.353268167413528,"score_spread":0.3143732558175176,"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."}}