{"id":"W2795622837","doi":"10.1016/j.ccell.2018.03.010","title":"Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas","year":2018,"lang":"en","type":"article","venue":"Cancer Cell","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":710,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; BC Cancer Agency; University of Calgary","funders":"National Human Genome Research Institute; National Institute on Alcohol Abuse and Alcoholism; National Cancer Institute; National Institutes of Health; Astex Pharmaceuticals; National Institute of Diabetes and Digestive and Kidney Diseases; Array BioPharma; Merck; Intramural Research Program; U.S. Department of Veterans Affairs","keywords":"Biology; MLH1; Microsatellite instability; KRAS; Genome instability; Genetics; Chromosome instability; Cancer research; Context (archaeology); Adenocarcinoma; Cancer; Colorectal cancer; DNA mismatch repair; Gene; DNA; DNA damage; Allele; Microsatellite; Chromosome","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":[0.0001688933,0.0001768922,0.0001991581,0.001725121,0.0004913686,0.0004533507,0.000291467,0.0003347496,0.004626366],"category_scores_gemma":[0.0003113936,0.0001755958,0.0003179168,0.0006474929,0.0002396825,0.0002328992,0.000310638,0.0003362837,0.0007870987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003354608,"about_ca_system_score_gemma":0.0002022226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001321792,"about_ca_topic_score_gemma":0.001818392,"domain_scores_codex":[0.9998512,0.0000209172,0.00001327747,0.0000354659,0.0000322129,0.00004689905],"domain_scores_gemma":[0.9998166,0.00004665862,0.00002705905,0.000026953,0.00004082987,0.00004184303],"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":[0.0005204162,0.00003393005,0.005644539,0.00006069245,0.00003390857,0.000656608,0.00006557482,0.00006070784,0.9883334,0.0005924127,0.0001548573,0.003842971],"study_design_scores_gemma":[0.00006178476,0.0006886468,0.3342876,0.00002409684,0.0002486177,0.01049759,0.0006827451,0.001280247,0.6224051,0.0005795265,0.02922609,0.00001789984],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903672,0.001653842,0.001611541,0.0001313963,0.00003207615,0.00002995066,0.0008645506,0.00006364491,0.005245761],"genre_scores_gemma":[0.9918579,0.0009547308,0.002120069,0.00006909527,0.00001474782,0.00002460758,0.001695744,0.00003206142,0.003231026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004626366,"threshold_uncertainty_score":0.0154767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03324264485780736,"score_gpt":0.3280796081842385,"score_spread":0.2948369633264311,"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."}}