{"id":"W4307272169","doi":"10.3389/fgene.2022.893832","title":"From the patient to the population: Use of genomics for population screening","year":2022,"lang":"en","type":"article","venue":"Frontiers in Genetics","topic":"Genetic factors in colorectal cancer","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"Lynch syndrome; Population; Genetic testing; Medicine; Genomics; Genomic medicine; Intensive care medicine; Genetics; Cancer; Environmental health; Biology; Computational biology; Internal medicine; Genome; 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":[0.0668295,0.0007757151,0.002089757,0.00609836,0.001379223,0.006481723,0.001925997,0.003770463,0.004051466],"category_scores_gemma":[0.1623837,0.0005973479,0.001550528,0.00411852,0.01009014,0.01378299,0.005108945,0.007898536,0.0005435173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004377801,"about_ca_system_score_gemma":0.01051654,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01159919,"about_ca_topic_score_gemma":0.01609931,"domain_scores_codex":[0.9354309,0.05380616,0.003431914,0.002321278,0.004432096,0.0005777109],"domain_scores_gemma":[0.8341783,0.1510652,0.004115844,0.003463191,0.006048155,0.001129343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002041016,0.0000524705,0.01896949,0.01590213,0.0008325159,0.0005512314,0.01003498,0.0008910442,0.0002907073,0.3276533,0.04228266,0.5823353],"study_design_scores_gemma":[0.000122376,0.0003120416,0.02223212,0.09411676,0.00142681,0.001738023,0.01128445,0.00184798,0.0005929876,0.4670597,0.3990373,0.0002294058],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.004312513,0.4585525,0.03453571,0.4854909,0.004398132,0.0001648294,0.0004060292,0.00009692935,0.01204245],"genre_scores_gemma":[0.2384466,0.4660551,0.05554757,0.2276045,0.009564822,0.0008961494,0.0004033568,0.0001436276,0.001338104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0668295,"threshold_uncertainty_score":0.3534324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03264274691579916,"score_gpt":0.2635125796542784,"score_spread":0.2308698327384792,"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."}}