{"id":"W4206450812","doi":"10.1093/jnci/djac003","title":"Risk Stratification for Early-Onset Colorectal Cancer Using a Combination of Genetic and Environmental Risk Scores: An International Multi-Center Study","year":2022,"lang":"en","type":"article","venue":"JNCI Journal of the National Cancer Institute","topic":"Colorectal Cancer Screening and Detection","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"National Cancer Institute; Cancer Research UK; Agency for Healthcare Research and Quality; World Health Organization","keywords":"Medicine; Confidence interval; Odds ratio; Percentile; Demography; Colorectal cancer; Receiver operating characteristic; Risk assessment; Relative risk; Internal medicine; Absolute risk reduction; Framingham Risk Score; Area under the curve; Incidence (geometry); Cancer; Statistics","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":[0.005007085,0.001322725,0.0007329409,0.001354825,0.0008950236,0.001080426,0.0008703155,0.0009276545,0.001019502],"category_scores_gemma":[0.006425804,0.0007730132,0.001451117,0.002021485,0.0005924312,0.0007277094,0.001154477,0.001261224,0.0002126472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004608951,"about_ca_system_score_gemma":0.0004051671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008190001,"about_ca_topic_score_gemma":0.006298321,"domain_scores_codex":[0.9979572,0.001004527,0.0001267044,0.0005622995,0.0001930707,0.0001561927],"domain_scores_gemma":[0.9948013,0.001147058,0.001724781,0.00110135,0.0005219954,0.0007035753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005253074,0.0000771641,0.9972342,0.000009161878,0.0004233889,0.00006407606,0.0001251869,0.0001929295,0.0001805368,0.00002712582,0.000114598,0.001026328],"study_design_scores_gemma":[0.00006222101,0.0002316613,0.9974442,0.00001256191,0.0003706376,0.0002587306,0.0001287032,0.001194437,0.00006903132,0.00004785286,0.0001665354,0.00001351049],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998468,0.0002126257,0.0007250906,0.00005290487,0.000007775685,0.00002333728,0.0003000385,0.000006126315,0.0002041711],"genre_scores_gemma":[0.9987533,0.0001002998,0.0005312927,0.00002715124,0.00001768117,0.00002064579,0.0004623899,0.000005540953,0.00008162834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008190001,"threshold_uncertainty_score":0.02648032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05477683729827725,"score_gpt":0.3456474304618954,"score_spread":0.2908705931636181,"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."}}