{"id":"W4386864391","doi":"10.1186/s13073-023-01229-9","title":"Identification of novel protein biomarkers and drug targets for colorectal cancer by integrating human plasma proteome with genome","year":2023,"lang":"en","type":"review","venue":"Genome Medicine","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Global Health Research","funders":"Science Fund for Distinguished Young Scholars of Zhejiang Province; Medical Research Council; National Natural Science Foundation of China; Cancer Research UK","keywords":"Proteome; Genome-wide association study; Biology; Proteomics; Mendelian randomization; Computational biology; Bioinformatics; Cancer research; Genetics; Medicine; Gene; Single-nucleotide polymorphism; Genotype","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":[0.0009621577,0.0003330747,0.001065086,0.0001349777,0.0001289713,0.00000763832,0.0002199576,0.0002791515,0.00000852722],"category_scores_gemma":[0.0002822204,0.0002370747,0.0001089215,0.0002083356,0.0002464903,0.000002280691,0.0000821108,0.0001328072,0.00000103248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006192595,"about_ca_system_score_gemma":0.0001687189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001406132,"about_ca_topic_score_gemma":0.0001528373,"domain_scores_codex":[0.998031,0.00009739325,0.0008620693,0.0005740071,0.0001286618,0.00030683],"domain_scores_gemma":[0.9984691,0.00005584793,0.0009878231,0.0002348894,0.0001677794,0.00008456997],"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":[0.0000604858,0.0000813033,0.00008276159,0.0112123,0.00152645,9.56127e-7,0.0002629316,0.000009995937,0.9536366,0.00003272707,0.001284931,0.03180859],"study_design_scores_gemma":[0.003564526,0.002395664,0.0007579072,0.005669011,0.00182571,0.0000349293,0.0005801665,0.000116114,0.003186919,0.00006702664,0.9805147,0.001287302],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03311455,0.9589717,0.002544263,0.0002112688,0.0001009225,0.004018784,0.0009911509,0.00001739812,0.00002998359],"genre_scores_gemma":[0.006326881,0.9788066,0.001745553,0.00002685993,0.0005642717,0.004356205,0.005752188,0.0001371025,0.002284319],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9792298,"threshold_uncertainty_score":0.9667625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290785792995439,"score_gpt":0.3276899001290278,"score_spread":0.2986113208294839,"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."}}