{"id":"W2608101186","doi":"10.1146/annurev-cancerbio-030617-050240","title":"The Impact of the Gut Microbiome on Colorectal Cancer","year":2017,"lang":"en","type":"article","venue":"Annual Review of Cancer Biology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Colorectal cancer; Microbiome; Gut flora; Cancer; Immune system; Carcinogenesis; Mouse model of colorectal and intestinal cancer; Inflammation; Gut microbiome; Etiology; Biology; Incidence (geometry); Innate immune system; Immunology; Medicine; Bioinformatics; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002921936,0.0001392749,0.0003059661,0.00001106161,0.0002351401,0.000006064024,0.0006938665,0.0001173687,0.00004481515],"category_scores_gemma":[0.0001676521,0.00006568952,0.0002839885,0.00004355217,0.0005077084,0.000002901338,0.0001887825,0.00009973744,0.000002924094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003317168,"about_ca_system_score_gemma":0.000445161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001796883,"about_ca_topic_score_gemma":0.0007175742,"domain_scores_codex":[0.9990687,0.0001245342,0.0003083735,0.0002066819,0.00004695494,0.0002447512],"domain_scores_gemma":[0.9985622,0.00002484408,0.000553153,0.0006174587,0.0002044682,0.00003790436],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001204874,0.00003326186,0.01542249,0.000392651,0.0001629676,1.090547e-7,0.00002849727,0.000001499215,0.9351775,0.0001731946,0.02663169,0.02185562],"study_design_scores_gemma":[0.0005525994,0.001112865,0.4210027,0.002023853,0.00007322575,0.000007114471,0.0000179594,7.579423e-7,0.1489161,0.00006872846,0.4260045,0.0002196603],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8297279,0.164843,0.000001075466,0.003071607,0.0004671332,0.0004009225,0.0008458389,0.00000186782,0.0006406786],"genre_scores_gemma":[0.765969,0.2328327,0.000005264691,0.0007458561,0.0001471686,0.00003582098,0.00001834384,0.000008808588,0.0002370245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7862614,"threshold_uncertainty_score":0.2716362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01139791673738228,"score_gpt":0.3970974882328043,"score_spread":0.3856995714954221,"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."}}