{"id":"W2794520982","doi":"10.1101/267666","title":"Ability of known susceptibility SNPs to predict colorectal cancer risk for persons with and without a family history","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital; Cancer Care Ontario","funders":"National Cancer Institute","keywords":"Family history; Single-nucleotide polymorphism; SNP; Colorectal cancer; Medicine; First-degree relatives; Oncology; Cancer; Internal medicine; Genetics; Genotype; Biology; Gene","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":[0.002283816,0.0004200213,0.0003164333,0.000938923,0.0002662305,0.0006098269,0.0004201032,0.0006628082,0.002036906],"category_scores_gemma":[0.009537028,0.0001999326,0.001145845,0.0004557986,0.0003088244,0.0003275787,0.0004375746,0.0006870531,0.0003726059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001797081,"about_ca_system_score_gemma":0.000155651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002972886,"about_ca_topic_score_gemma":0.00248665,"domain_scores_codex":[0.9986241,0.0005942649,0.0001117718,0.0004577572,0.0001309163,0.00008111163],"domain_scores_gemma":[0.9931416,0.004071056,0.00147862,0.0006569478,0.0003046891,0.0003471365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001479215,0.00001723305,0.9973901,0.000006481675,0.0001985344,0.00004277457,0.00001950458,0.0007055001,0.0002090034,0.00001904536,0.00004166297,0.001202317],"study_design_scores_gemma":[0.00001351468,0.0001350964,0.9938195,0.000007869916,0.0001816382,0.000335784,0.00004076912,0.0048218,0.0003325234,0.0001539582,0.0001487016,0.000008903728],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971572,0.0003295683,0.001391727,0.00006354076,0.00001117244,0.000008437871,0.0005064293,0.00002061922,0.0005113254],"genre_scores_gemma":[0.9992784,0.000029038,0.0003740476,0.00001407189,0.000005739584,0.000003738289,0.0002077991,0.000002130958,0.0000852199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002972886,"threshold_uncertainty_score":0.01207811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958294620557752,"score_gpt":0.2522297734255887,"score_spread":0.2326468272200112,"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."}}