{"id":"W3129379232","doi":"10.1038/s41588-021-00791-5","title":"The NCI Genomic Data Commons","year":2021,"lang":"pl","type":"article","venue":"Nature Genetics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":211,"is_retracted":false,"has_abstract":false,"ca_institutions":"Terahertz Technology Solutions (Canada); Centre Hospitalier Universitaire Sainte-Justine; Ontario Institute for Cancer Research","funders":"National Cancer Institute","keywords":"Biology; Petabyte; Genomics; Commons; Interface (matter); Cancer; Computational biology; Genetics; Big data; Genome; Data mining; Gene; Computer science","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003569677,0.0003836929,0.000280135,0.00002330272,0.0005389089,0.0003505993,0.00188518,0.001060441,0.00004516997],"category_scores_gemma":[0.0006177918,0.0003468779,0.0001633127,0.0002074085,0.0002523414,0.000003034376,0.003144574,0.0009533043,0.00006909463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006371398,"about_ca_system_score_gemma":0.001401494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001146754,"about_ca_topic_score_gemma":0.001602559,"domain_scores_codex":[0.9974435,0.000136035,0.0004565026,0.0009938068,0.0002995448,0.0006705997],"domain_scores_gemma":[0.9949202,0.0001809802,0.0001881237,0.004096584,0.0003823079,0.0002318209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002474663,0.0004651836,0.01692821,0.00013891,0.001327724,0.0002354161,0.0001445052,0.0006868255,0.1726538,0.002061467,0.7127538,0.09235664],"study_design_scores_gemma":[0.0005880974,0.0001167249,0.006309347,0.00001939517,0.0002064419,0.0000772798,0.00009395189,0.0005745162,0.04064469,0.0002592067,0.9506755,0.0004348471],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.3666807,0.6133723,0.0003545887,0.005296027,0.005939668,0.0003726788,0.003471018,0.00001494224,0.004498096],"genre_scores_gemma":[0.8536838,0.1309129,0.001850023,0.00331119,0.00335939,0.000009454508,0.003449524,0.000102122,0.003321652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.487003,"threshold_uncertainty_score":0.9998983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135941745023802,"score_gpt":0.275273594384021,"score_spread":0.2616794198816408,"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."}}