{"id":"W2963414887","doi":"10.1016/j.cels.2019.06.006","title":"Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data","year":2019,"lang":"en","type":"article","venue":"Cell Systems","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":199,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"National Institute of Environmental Health Sciences; National Cancer Institute","keywords":"Computational biology; Computer science; Biology","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":[0.0001770554,0.0001171088,0.0002555734,0.00002037376,0.0000274212,0.00006818249,0.0004569481,0.00008997172,0.000005495576],"category_scores_gemma":[0.00001792504,0.0001132786,0.00001373492,0.00002481065,0.0000608935,0.00000914777,0.001260797,0.00005544024,0.000007014568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000736376,"about_ca_system_score_gemma":0.00005582797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003665992,"about_ca_topic_score_gemma":0.0003411912,"domain_scores_codex":[0.9990892,0.00003083755,0.0002515648,0.0004252537,0.00006513599,0.0001379524],"domain_scores_gemma":[0.9982617,0.00002157494,0.0001257991,0.00149265,0.00002765373,0.00007065145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000222749,0.0001207606,0.6788963,0.0007194218,0.0001126959,0.000003839116,0.0002348334,0.00004456674,0.305273,0.00006585817,0.01096666,0.003339319],"study_design_scores_gemma":[0.006437118,0.001153658,0.1248898,0.0002321681,0.0003307067,0.00005667279,0.00181844,0.03252676,0.03047798,0.0000294834,0.8009695,0.001077658],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792843,0.01875241,0.0000947372,0.00002973561,0.0002994802,0.0003093911,0.0008533943,0.000003742083,0.0003728489],"genre_scores_gemma":[0.9975926,0.000472017,0.0001367964,0.00002670506,0.000137556,0.00000550022,0.001385957,0.00001895035,0.0002238632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7900029,"threshold_uncertainty_score":0.4619367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620257314073815,"score_gpt":0.2697130753048708,"score_spread":0.2435105021641327,"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."}}